资源概述
本资源包汇集了2025年聚客大模型三期（第一期、第二期、第三期）的全面学习资料，内容丰富，覆盖了Python编程、AI基础、LLM（大型语言模型）应用、LangChain和RAG（Retrieval-Augmented Generation）技术、多模态数据处理等多个前沿技术领域。
主要内容
- Python基础：包括Python编程基础、字符串处理、文件IO、异常处理等。
- AI及LLM基础：介绍AI领域的基础概念和LLM技术。
- LangChain和RAG实战：深入讲解LangChain和RAG技术的实际应用。
- 多模态：探讨多模态大模型的概念与本地部署调用。
- 其他相关技术：如Hugging Face、AutoGen Studio、Llama3、LangGraph等。
适用场景
本资源适合AI和机器学习爱好者、开发者、以及希望提升自身技术能力的专业人士学习使用。
亮点
- 内容全面：涵盖AI和机器学习领域的多个前沿技术。
- 实战性强：提供大量实战案例，帮助学习者快速掌握技术。
- 更新及时：紧跟AI和机器学习领域的最新发展。
📂 资源目录
📁 06_LangChain进阶
📁 day10_自定义组件专题
【课件】自定义组件专题.pdf [858.0 KB]
【资料】自定义组件专题.pdf [2.2 MB]
【录播】自定义组件专题.mp4 [830.9 MB]
【语雀】自定义组件专题.txt [107.0 B]
day10-demo.zip [18.7 KB]
【MD】自定义组件专题.md [48.7 KB]
06_LangChain进阶说明.zip [1.8 MB]
📁 07_langChain和RAG实战
📁 day11_基于LangChain和RAG的常用案例实战
【资料】基于LangChain和RAG的常用案例实战.pdf [5.4 MB]
【语雀】基于LangChain和RAG的常用案例实战.txt [128.0 B]
【课件】基于LangChain和RAG的常用案例实战.pdf [863.5 KB]
day11-demo.zip [2.1 MB]
【录播】基于LangChain和RAG的常用案例实战.mp4 [817.6 MB]
【MD】基于LangChain和RAG的常用案例实战.md [28.1 KB]
07_langChain和RAG实战必看.png [493.5 KB]
📁 02_Prompt基础
📁 day04_Prompt Engineering 提示词工程
ChatGPT提示技巧工程完全指南.pdf [2.9 MB]
实用Prompt指令大全.xlsx [6.2 MB]
【资料】Prompt Engineering 提示词工程.pdf [2.6 MB]
day4-demo.zip [106.0 KB]
【MD】Prompt Engineering 提示词工程.md [25.0 KB]
【语雀】Prompt Engineering 提示词工程.txt [121.0 B]
DALL-E-3绘图提示词大全.pdf [14.3 MB]
【录播】Prompt Engineering 提示词工程.mp4 [1.3 GB]
【课件】Prompt Engineering 提示词工程.pdf [826.4 KB]
02_Prompt基础资料.zip [1.8 MB]
📁 16_项目实战（聚客第三期_最新）
📁 day08_GPT2-中文生成模型定制化微调训练
📁 demo_8
📁 .idea
📁 inspectionProfiles
profiles_settings.xml [174.0 B]
modules.xml [271.0 B]
workspace.xml [7.2 KB]
misc.xml [189.0 B]
.gitignore [50.0 B]
demo_8.iml [291.0 B]
📁 params
📁 example
test03.py [824.0 B]
test04.py [844.0 B]
test02.py [835.0 B]
test05.py [818.0 B]
test01.py [864.0 B]
📁 __pycache__
data.cpython-312.pyc [1.3 KB]
📁 data
chinese_poems.txt [49.3 MB]
data.py [496.0 B]
train.py [4.6 KB]
day08_GPT2-中文生成模型定制化微调训练必看.png [493.5 KB]
【课件】Hugging Face 模型微调训练（GPT2-中文生成模型定制化微调训练）.pdf [510.3 KB]
【录播】GPT2-中文生成模型定制化微调训练.mp4 [871.5 MB]
📁 day12_Lora模型合并与推理测试
📁 checkpoint-800
README.md [5.0 KB]
training_args.bin [5.5 KB]
special_tokens_map.json [650.0 B]
adapter_model.safetensors [21.5 MB]
adapter_config.json [754.0 B]
tokenizer.json [16.4 MB]
tokenizer_config.json [53.4 KB]
optimizer.pt [43.2 MB]
scheduler.pt [1.0 KB]
trainer_state.json [29.3 KB]
rng_state.pth [13.9 KB]
📁 data
ruozhiba_qaswift.json [588.5 KB]
day12_Lora模型合并与推理测试文档.zip [1.8 MB]
【录播】Lora模型合并与推理测试.mp4 [906.6 MB]
📁 1_开班典礼-241216
2024-12-16 开班典礼.mp4 [277.3 MB]
📁 day24_多模态大模型
📁 笔记
多模态01.png [86.8 KB]
多模态02.png [127.3 KB]
【资料】多模态（多模态大模型的概念与本地部署调用）.pdf [4.9 MB]
【课件】多模态（多模态大模型的概念与本地部署调用）.pdf [731.9 KB]
【录播】多模态大模型的概念与本地部署调用.mp4 [704.8 MB]
📁 day29_基于RAG的法律条文助手（实现篇）
📁 项目源码
📁 rag_law
📁 data
data1.json [64.4 KB]
read_json.py [781.0 B]
llama_index_vllm.py [873.0 B]
llama_index_llm.py [583.0 B]
rag_law.py [8.0 KB]
【课件】基于RAG的法律条文智能助手（实现篇）.pdf [491.2 KB]
【录播】基于RAG的法律条文智能助手【实现篇】.mp4 [1.5 GB]
📁 day13_LLaMA-Factory模型导出量化
📁 checkpoint-3700
README.md [5.0 KB]
trainer_state.json [133.8 KB]
adapter_model.safetensors [21.5 MB]
special_tokens_map.json [439.0 B]
tokenizer.json [16.4 MB]
adapter_config.json [754.0 B]
optimizer.pt [43.2 MB]
tokenizer_config.json [53.3 KB]
scheduler.pt [1.0 KB]
training_args.bin [5.4 KB]
rng_state.pth [13.9 KB]
📁 demo_13
📁 data
ruozhiba_qaswift_train.json [632.3 KB]
ruozhiba_qaswift.json [588.5 KB]
test01.py [724.0 B]
【课件】LLaMa3导出量化（LLaMA-Factory模型导出量化）.pdf [497.3 KB]
【资料】LLaMa3导出量化（LLaMA-Factory模型导出量化）.pdf [769.0 KB]
【录播】LLaMA-Factory模型导出量化.mp4 [1.1 GB]
📁 day19_OpenCompass大模型评估
📁 ptb
📁 ptb_val
data-00000-of-00001.arrow [394.6 KB]
dataset_info.json [2.1 KB]
state.json [267.0 B]
📁 ptb_train
state.json [262.0 B]
dataset_info.json [2.1 KB]
data-00000-of-00001.arrow [4.9 MB]
📁 如果OpenCompassData-core-20240207.zip压缩包下载解压有问题就用当前目录对应的解压包
📁 OpenCompassData-core-20240207
📁 data
📁 FewCLUE
📁 iflytek
test_public.json [1.5 MB]
dev_4.json [596.5 KB]
dev_3.json [608.4 KB]
dev_1.json [590.6 KB]
dev_2.json [598.5 KB]
dev_few_all.json [1.1 MB]
unlabeled.json [5.8 MB]
train_3.json [819.8 KB]
train_few_all.json [2.6 MB]
train_1.json [801.1 KB]
train_0.json [815.7 KB]
dev_0.json [593.0 KB]
train_4.json [817.8 KB]
label_id2des_desc2short.py [5.3 KB]
train_2.json [832.6 KB]
test.json [2.0 MB]
📁 csldcp
train_few_all.json [1.2 MB]
train_0.json [322.2 KB]
train_4.json [321.4 KB]
test_public.json [1.0 MB]
dev_0.json [322.0 KB]
test.json [1.7 MB]
dev_4.json [311.1 KB]
labels_all.txt [1.1 KB]
train_3.json [319.0 KB]
unlabeled.json [10.1 MB]
dev_3.json [324.8 KB]
labelDesc2label.py [2.5 KB]
dev_2.json [323.7 KB]
train_1.json [327.1 KB]
train_2.json [317.2 KB]
dev_1.json [318.1 KB]
dev_few_all.json [1.2 MB]
📁 cluewsc
label_distribution.json [407.0 B]
dev_0.json [10.1 KB]
test_public.json [314.2 KB]
train_4.json [10.2 KB]
dev_1.json [10.9 KB]
dev_4.json [10.7 KB]
dev_2.json [10.1 KB]
train_3.json [10.5 KB]
train_0.json [10.6 KB]
test.json [86.6 KB]
train_2.json [9.9 KB]
train_few_all.json [52.1 KB]
unlabeled.json
train_1.json [10.7 KB]
dev_few_all.json [52.4 KB]
dev_3.json [10.9 KB]
📁 eprstmt
test_public.json [111.9 KB]
train_4.json [4.8 KB]
test.json [127.6 KB]
dev_1.json [6.1 KB]
train_2.json [6.2 KB]
dev_public.json [634.0 B]
train_1.json [5.7 KB]
unlabeled.json [3.1 MB]
train_3.json [5.5 KB]
dev_few_all.json [30.4 KB]
dev_0.json [6.6 KB]
train_few_all.json [27.2 KB]
train_0.json [4.8 KB]
dev_2.json [7.0 KB]
dev_4.json [5.8 KB]
dev_3.json [4.7 KB]
📁 csl
test.json [2.4 MB]
dev_1.json [26.3 KB]
test_public.json [2.3 MB]
dev_4.json [27.1 KB]
dev_0.json [23.8 KB]
unlabeled.json [15.9 MB]
train_1.json [27.2 KB]
train_2.json [25.5 KB]
train_4.json [26.8 KB]
train_3.json [23.5 KB]
dev_3.json [29.8 KB]
train_few_all.json [130.0 KB]
dev_2.json [24.6 KB]
dev_few_all.json [131.8 KB]
train_0.json [27.0 KB]
📁 chid
train_2.json [19.3 KB]
test.json [891.6 KB]
dev_2.json [19.2 KB]
train_4.json [19.5 KB]
dev_few_all.json [91.8 KB]
dev_1.json [19.2 KB]
dev_4.json [19.2 KB]
dev_0.json [19.0 KB]
train_1.json [19.6 KB]
test_public.json [918.2 KB]
train_0.json [19.1 KB]
dev_3.json [18.9 KB]
train_few_all.json [92.8 KB]
train_3.json [18.9 KB]
unlabeled.json [3.3 MB]
📁 tnews
test.json [136.9 KB]
train_1.json [45.4 KB]
dev_0.json [45.9 KB]
unlabeled.json [3.0 MB]
dev_3.json [46.5 KB]
train_3.json [46.0 KB]
test_public.json [177.1 KB]
train_2.json [43.8 KB]
label_index2en2zh.json [992.0 B]
dev_1.json [46.0 KB]
dev_few_all.json [209.4 KB]
train_4.json [46.1 KB]
train_few_all.json [225.2 KB]
train_0.json [46.8 KB]
dev_4.json [45.2 KB]
dev_2.json [45.4 KB]
📁 bustm
train_4.json [3.3 KB]
dev_1.json [3.1 KB]
train_2.json [3.2 KB]
train_0.json [3.1 KB]
train_3.json [3.2 KB]
unlabeled.json [372.6 KB]
test_public.json [180.5 KB]
dev_4.json [3.2 KB]
train_1.json [3.2 KB]
dev_2.json [3.3 KB]
dev_3.json [3.2 KB]
test.json [175.5 KB]
dev_0.json [3.2 KB]
dev_few_all.json [16.1 KB]
train_few_all.json [16.0 KB]
📁 ocnli
dev_3.json [10.8 KB]
train_0.json [9.5 KB]
train_3.json [9.5 KB]
train_4.json [9.6 KB]
train_1.json [10.1 KB]
train_few_all.json [48.2 KB]
dev_few_all.json [55.1 KB]
dev_2.json [10.9 KB]
test.json [445.3 KB]
test_public.json [861.3 KB]
dev_1.json [11.5 KB]
dev_0.json [10.7 KB]
unlabeled.json [5.5 MB]
dev_4.json [11.1 KB]
train_2.json [9.4 KB]
readme.md [906.0 B]
📁 mmlu
📁 val
global_facts_val.csv [1.6 KB]
college_mathematics_val.csv [2.3 KB]
college_chemistry_val.csv [2.1 KB]
professional_medicine_val.csv [22.6 KB]
abstract_algebra_val.csv [1.7 KB]
high_school_microeconomics_val.csv [6.8 KB]
econometrics_val.csv [4.6 KB]
college_physics_val.csv [3.2 KB]
high_school_computer_science_val.csv [3.1 KB]
public_relations_val.csv [4.2 KB]
human_sexuality_val.csv [2.1 KB]
nutrition_val.csv [7.5 KB]
high_school_macroeconomics_val.csv [11.7 KB]
moral_scenarios_val.csv [40.0 KB]
security_studies_val.csv [21.6 KB]
human_aging_val.csv [4.0 KB]
high_school_physics_val.csv [6.2 KB]
moral_disputes_val.csv [11.3 KB]
clinical_knowledge_val.csv [5.8 KB]
us_foreign_policy_val.csv [2.9 KB]
medical_genetics_val.csv [2.7 KB]
prehistory_val.csv [9.3 KB]
electrical_engineering_val.csv [2.5 KB]
international_law_val.csv [6.0 KB]
sociology_val.csv [6.5 KB]
high_school_world_history_val.csv [43.9 KB]
business_ethics_val.csv [2.7 KB]
marketing_val.csv [6.6 KB]
management_val.csv [1.5 KB]
college_computer_science_val.csv [4.3 KB]
elementary_mathematics_val.csv [7.8 KB]
professional_accounting_val.csv [13.4 KB]
logical_fallacies_val.csv [4.6 KB]
high_school_biology_val.csv [10.0 KB]
astronomy_val.csv [4.5 KB]
high_school_chemistry_val.csv [6.4 KB]
computer_security_val.csv [4.2 KB]
high_school_european_history_val.csv [28.6 KB]
professional_law_val.csv [195.9 KB]
miscellaneous_val.csv [12.0 KB]
high_school_statistics_val.csv [9.3 KB]
high_school_psychology_val.csv [15.5 KB]
conceptual_physics_val.csv [3.7 KB]
high_school_us_history_val.csv [30.5 KB]
virology_val.csv [4.9 KB]
college_medicine_val.csv [7.2 KB]
high_school_geography_val.csv [3.7 KB]
anatomy_val.csv [2.7 KB]
world_religions_val.csv [2.3 KB]
jurisprudence_val.csv [3.4 KB]
philosophy_val.csv [8.2 KB]
formal_logic_val.csv [5.8 KB]
college_biology_val.csv [4.3 KB]
professional_psychology_val.csv [26.8 KB]
high_school_government_and_politics_val.csv [6.4 KB]
machine_learning_val.csv [2.9 KB]
high_school_mathematics_val.csv [5.0 KB]
📁 test
world_religions_test.csv [20.7 KB]
medical_genetics_test.csv [18.1 KB]
high_school_psychology_test.csv [143.1 KB]
international_law_test.csv [49.5 KB]
business_ethics_test.csv [30.7 KB]
us_foreign_policy_test.csv [25.4 KB]
college_chemistry_test.csv [21.8 KB]
professional_accounting_test.csv [115.7 KB]
college_medicine_test.csv [76.5 KB]
formal_logic_test.csv [45.8 KB]
miscellaneous_test.csv [126.2 KB]
abstract_algebra_test.csv [17.0 KB]
global_facts_test.csv [15.8 KB]
high_school_us_history_test.csv [286.0 KB]
virology_test.csv [33.9 KB]
clinical_knowledge_test.csv [55.2 KB]
sociology_test.csv [60.1 KB]
electrical_engineering_test.csv [21.1 KB]
philosophy_test.csv [71.1 KB]
high_school_biology_test.csv [100.0 KB]
public_relations_test.csv [25.6 KB]
moral_disputes_test.csv [97.6 KB]
human_aging_test.csv [39.7 KB]
anatomy_test.csv [29.1 KB]
high_school_microeconomics_test.csv [68.5 KB]
astronomy_test.csv [42.0 KB]
econometrics_test.csv [43.0 KB]
college_physics_test.csv [27.2 KB]
marketing_test.csv [56.1 KB]
college_computer_science_test.csv [39.5 KB]
college_mathematics_test.csv [21.9 KB]
high_school_geography_test.csv [36.5 KB]
logical_fallacies_test.csv [45.2 KB]
moral_scenarios_test.csv [353.0 KB]
human_sexuality_test.csv [28.4 KB]
professional_law_test.csv [1.8 MB]
jurisprudence_test.csv [30.6 KB]
high_school_european_history_test.csv [260.6 KB]
security_studies_test.csv [195.1 KB]
high_school_chemistry_test.csv [52.7 KB]
high_school_macroeconomics_test.csv [105.9 KB]
professional_psychology_test.csv [207.4 KB]
college_biology_test.csv [44.3 KB]
high_school_mathematics_test.csv [47.4 KB]
elementary_mathematics_test.csv [60.2 KB]
nutrition_test.csv [83.9 KB]
high_school_world_history_test.csv [365.0 KB]
MMLU_test_contamination_annotations.json [641.3 KB]
high_school_physics_test.csv [54.9 KB]
high_school_statistics_test.csv [103.5 KB]
conceptual_physics_test.csv [34.2 KB]
high_school_government_and_politics_test.csv [60.1 KB]
high_school_computer_science_test.csv [41.3 KB]
prehistory_test.csv [80.3 KB]
computer_security_test.csv [24.3 KB]
management_test.csv [17.0 KB]
professional_medicine_test.csv [206.6 KB]
machine_learning_test.csv [31.0 KB]
📁 dev
astronomy_dev.csv [1.9 KB]
global_facts_dev.csv [1.1 KB]
public_relations_dev.csv [1.3 KB]
moral_scenarios_dev.csv [1.9 KB]
college_mathematics_dev.csv [1.3 KB]
management_dev.csv [761.0 B]
computer_security_dev.csv [974.0 B]
electrical_engineering_dev.csv [851.0 B]
high_school_physics_dev.csv [1.3 KB]
college_medicine_dev.csv [1.5 KB]
clinical_knowledge_dev.csv [1.1 KB]
world_religions_dev.csv [540.0 B]
high_school_government_and_politics_dev.csv [1.6 KB]
human_aging_dev.csv [880.0 B]
high_school_microeconomics_dev.csv [1.1 KB]
abstract_algebra_dev.csv [719.0 B]
college_computer_science_dev.csv [2.6 KB]
miscellaneous_dev.csv [562.0 B]
high_school_european_history_dev.csv [11.2 KB]
college_chemistry_dev.csv [1.2 KB]
philosophy_dev.csv [859.0 B]
prehistory_dev.csv [1.7 KB]
high_school_biology_dev.csv [1.5 KB]
anatomy_dev.csv [830.0 B]
college_biology_dev.csv [1.4 KB]
econometrics_dev.csv [1.5 KB]
college_physics_dev.csv [1.2 KB]
high_school_us_history_dev.csv [8.6 KB]
high_school_mathematics_dev.csv [1.1 KB]
elementary_mathematics_dev.csv [1.3 KB]
marketing_dev.csv [1.3 KB]
sociology_dev.csv [1.4 KB]
moral_disputes_dev.csv [1.6 KB]
high_school_world_history_dev.csv [4.7 KB]
formal_logic_dev.csv [1.6 KB]
us_foreign_policy_dev.csv [1.4 KB]
nutrition_dev.csv [1.9 KB]
jurisprudence_dev.csv [1.1 KB]
high_school_computer_science_dev.csv [2.7 KB]
professional_psychology_dev.csv [2.1 KB]
high_school_chemistry_dev.csv [1.1 KB]
high_school_macroeconomics_dev.csv [1.2 KB]
professional_medicine_dev.csv [3.6 KB]
high_school_psychology_dev.csv [1.7 KB]
machine_learning_dev.csv [2.1 KB]
conceptual_physics_dev.csv [799.0 B]
professional_accounting_dev.csv [2.0 KB]
human_sexuality_dev.csv [942.0 B]
logical_fallacies_dev.csv [1.4 KB]
international_law_dev.csv [2.2 KB]
virology_dev.csv [962.0 B]
high_school_geography_dev.csv [1.2 KB]
security_studies_dev.csv [5.1 KB]
high_school_statistics_dev.csv [2.4 KB]
medical_genetics_dev.csv [952.0 B]
business_ethics_dev.csv [2.0 KB]
professional_law_dev.csv [6.4 KB]
README.txt [1.5 KB]
possibly_contaminated_urls.txt [8.6 KB]
📁 LCSTS
test.src.txt [3.2 MB]
📁 winogrande
README.md [2.6 KB]
train_debiased-labels.lst [18.1 KB]
train_m-labels.lst [5.0 KB]
train_l-labels.lst [20.0 KB]
sample-submission-labels.lst [17.3 KB]
dev-labels.lst [2.5 KB]
train_xl.jsonl [8.3 MB]
train_m.jsonl [541.1 KB]
train_s.jsonl [135.4 KB]
train_xl-labels.lst [78.9 KB]
train_xs-labels.lst [320.0 B]
dev.jsonl [269.2 KB]
eval.py [2.0 KB]
train_xs.jsonl [34.0 KB]
train_s-labels.lst [1.3 KB]
test.jsonl [350.0 KB]
train_debiased.jsonl [1.9 MB]
train_l.jsonl [2.1 MB]
📁 strategyqa
strategyQA_train.json [1.2 MB]
📁 commonsenseqa
test_rand_split_no_answers.jsonl [413.2 KB]
dev_rand_split.jsonl [460.6 KB]
train_rand_split.jsonl [3.6 MB]
📁 hellaswag
hellaswag_train.jsonl [45.3 MB]
hellaswag_train_sampled25.jsonl [9.2 KB]
hellaswag_val_contamination_annotations.json [225.9 KB]
hellaswag.jsonl [7.9 MB]
📁 humaneval
human-eval-v2-20210705.jsonl [209.4 KB]
📁 BBH
📁 lib_prompt
movie_recommendation.txt [2.1 KB]
tracking_shuffled_objects_seven_objects.txt [2.5 KB]
hyperbaton.txt [3.0 KB]
tracking_shuffled_objects_three_objects.txt [2.5 KB]
date_understanding.txt [1.1 KB]
web_of_lies.txt [2.9 KB]
logical_deduction_seven_objects.txt [2.4 KB]
logical_deduction_three_objects.txt [2.4 KB]
geometric_shapes.txt [4.7 KB]
tracking_shuffled_objects_five_objects.txt [2.5 KB]
causal_judgement.txt [3.6 KB]
temporal_sequences.txt [3.0 KB]
word_sorting.txt [2.1 KB]
dyck_languages.txt [2.3 KB]
sports_understanding.txt [820.0 B]
reasoning_about_colored_objects.txt [2.2 KB]
formal_fallacies.txt [4.4 KB]
logical_deduction_five_objects.txt [2.4 KB]
penguins_in_a_table.txt [2.3 KB]
snarks.txt [3.0 KB]
disambiguation_qa.txt [3.5 KB]
multistep_arithmetic_two.txt [2.3 KB]
boolean_expressions.txt [1.7 KB]
ruin_names.txt [3.4 KB]
object_counting.txt [1.4 KB]
navigate.txt [2.1 KB]
salient_translation_error_detection.txt [6.0 KB]
📁 data
README.md [3.9 KB]
disambiguation_qa.json [88.6 KB]
logical_deduction_three_objects.json [115.0 KB]
logical_deduction_five_objects.json [157.2 KB]
object_counting.json [40.4 KB]
temporal_sequences.json [150.1 KB]
geometric_shapes.json [80.8 KB]
hyperbaton.json [49.0 KB]
navigate.json [59.3 KB]
tracking_shuffled_objects_five_objects.json [171.1 KB]
reasoning_about_colored_objects.json [101.8 KB]
multistep_arithmetic_two.json [19.7 KB]
dyck_languages.json [48.2 KB]
ruin_names.json [57.3 KB]
boolean_expressions.json [18.2 KB]
salient_translation_error_detection.json [285.1 KB]
formal_fallacies.json [147.5 KB]
penguins_in_a_table.json [75.9 KB]
word_sorting.json [70.1 KB]
sports_understanding.json [33.3 KB]
causal_judgement.json [202.2 KB]
snarks.json [45.5 KB]
date_understanding.json [65.7 KB]
tracking_shuffled_objects_seven_objects.json [215.3 KB]
web_of_lies.json [57.1 KB]
logical_deduction_seven_objects.json [199.1 KB]
tracking_shuffled_objects_three_objects.json [131.1 KB]
movie_recommendation.json [61.7 KB]
📁 nq
nq-dev.qa.csv [605.5 KB]
nq-test.qa.csv [290.0 KB]
📁 siqa
train.jsonl [7.7 MB]
train-labels.lst [65.3 KB]
dev.jsonl [463.3 KB]
dev-labels.lst [3.8 KB]
📁 ARC
📁 ARC-c
ARC-Challenge-Test.jsonl [481.2 KB]
ARC-Challenge-Dev.jsonl [123.6 KB]
ARC_c_test_contamination_annotations.json [64.2 KB]
📁 ARC-e
ARC-Easy-Test.jsonl [874.1 KB]
ARC-Easy-Dev.jsonl [209.4 KB]
📁 cmmlu
📁 dev
nutrition.csv [440.0 B]
chinese_teacher_qualification.csv [835.0 B]
elementary_commonsense.csv [358.0 B]
high_school_biology.csv [1.1 KB]
elementary_mathematics.csv [357.0 B]
business_ethics.csv [424.0 B]
elementary_chinese.csv [446.0 B]
astronomy.csv [440.0 B]
college_actuarial_science.csv [813.0 B]
chinese_history.csv [1.1 KB]
chinese_driving_rule.csv [688.0 B]
chinese_literature.csv [484.0 B]
legal_and_moral_basis.csv [677.0 B]
public_relations.csv [466.0 B]
arts.csv [388.0 B]
security_study.csv [569.0 B]
genetics.csv [508.0 B]
college_education.csv [593.0 B]
professional_law.csv [805.0 B]
professional_accounting.csv [547.0 B]
computer_security.csv [654.0 B]
elementary_information_and_technology.csv [436.0 B]
high_school_chemistry.csv [917.0 B]
philosophy.csv [511.0 B]
clinical_knowledge.csv [726.0 B]
college_mathematics.csv [832.0 B]
electrical_engineering.csv [442.0 B]
world_religions.csv [384.0 B]
high_school_politics.csv [1.4 KB]
international_law.csv [601.0 B]
college_law.csv [832.0 B]
high_school_physics.csv [978.0 B]
sociology.csv [468.0 B]
global_facts.csv [562.0 B]
conceptual_physics.csv [1.1 KB]
high_school_geography.csv [613.0 B]
education.csv [448.0 B]
college_medicine.csv [432.0 B]
machine_learning.csv [722.0 B]
college_medical_statistics.csv [665.0 B]
virology.csv [430.0 B]
food_science.csv [437.0 B]
journalism.csv [415.0 B]
management.csv [535.0 B]
chinese_foreign_policy.csv [1.1 KB]
chinese_food_culture.csv [439.0 B]
high_school_mathematics.csv [468.0 B]
construction_project_management.csv [556.0 B]
traditional_chinese_medicine.csv [304.0 B]
college_engineering_hydrology.csv [513.0 B]
ancient_chinese.csv [700.0 B]
marxist_theory.csv [635.0 B]
marketing.csv [598.0 B]
professional_psychology.csv [498.0 B]
ethnology.csv [429.0 B]
chinese_civil_service_exam.csv [1.1 KB]
economics.csv [586.0 B]
human_sexuality.csv [508.0 B]
agronomy.csv [421.0 B]
sports_science.csv [463.0 B]
anatomy.csv [349.0 B]
computer_science.csv [441.0 B]
logical.csv [478.0 B]
modern_chinese.csv [565.0 B]
jurisprudence.csv [472.0 B]
professional_medicine.csv [429.0 B]
world_history.csv [1.5 KB]
📁 test
management.csv [35.3 KB]
elementary_chinese.csv [38.1 KB]
astronomy.csv [29.0 KB]
chinese_civil_service_exam.csv [74.6 KB]
construction_project_management.csv [25.2 KB]
genetics.csv [30.3 KB]
college_mathematics.csv [29.8 KB]
chinese_teacher_qualification.csv [44.0 KB]
conceptual_physics.csv [42.5 KB]
global_facts.csv [24.8 KB]
college_medicine.csv [46.6 KB]
arts.csv [18.0 KB]
college_law.csv [30.1 KB]
professional_psychology.csv [34.3 KB]
professional_accounting.csv [30.1 KB]
agronomy.csv [21.6 KB]
professional_law.csv [66.1 KB]
journalism.csv [25.0 KB]
chinese_driving_rule.csv [22.0 KB]
education.csv [22.1 KB]
high_school_politics.csv [58.0 KB]
economics.csv [28.4 KB]
computer_security.csv [42.8 KB]
professional_medicine.csv [54.9 KB]
ethnology.csv [20.8 KB]
electrical_engineering.csv [29.7 KB]
marxist_theory.csv [37.8 KB]
ancient_chinese.csv [26.5 KB]
anatomy.csv [15.1 KB]
marketing.csv [33.1 KB]
security_study.csv [24.4 KB]
high_school_biology.csv [68.9 KB]
philosophy.csv [17.5 KB]
chinese_foreign_policy.csv [40.0 KB]
traditional_chinese_medicine.csv [23.0 KB]
modern_chinese.csv [28.0 KB]
public_relations.csv [27.9 KB]
high_school_physics.csv [29.5 KB]
logical.csv [21.0 KB]
machine_learning.csv [27.7 KB]
chinese_literature.csv [32.6 KB]
high_school_geography.csv [28.2 KB]
sociology.csv [33.8 KB]
chinese_food_culture.csv [18.9 KB]
food_science.csv [17.2 KB]
business_ethics.csv [31.7 KB]
legal_and_moral_basis.csv [52.1 KB]
clinical_knowledge.csv [75.3 KB]
international_law.csv [40.8 KB]
high_school_chemistry.csv [46.3 KB]
college_actuarial_science.csv [23.2 KB]
chinese_history.csv [119.0 KB]
sports_science.csv [22.4 KB]
college_medical_statistics.csv [20.7 KB]
computer_science.csv [29.5 KB]
world_religions.csv [18.9 KB]
nutrition.csv [20.8 KB]
jurisprudence.csv [124.8 KB]
elementary_information_and_technology.csv [37.0 KB]
high_school_mathematics.csv [22.2 KB]
elementary_commonsense.csv [23.3 KB]
virology.csv [26.0 KB]
college_education.csv [23.0 KB]
college_engineering_hydrology.csv [18.8 KB]
elementary_mathematics.csv [30.6 KB]
human_sexuality.csv [19.2 KB]
world_history.csv [62.8 KB]
📁 AGIEval
📁 data
📁 v1
gaokao-english.jsonl [645.4 KB]
sat-en.jsonl [1.1 MB]
gaokao-mathcloze.jsonl [37.8 KB]
gaokao-chinese.jsonl [705.5 KB]
jec-qa-ca.jsonl [705.9 KB]
math.jsonl [881.5 KB]
lsat-lr.jsonl [601.2 KB]
sat-math.jsonl [273.9 KB]
gaokao-history.jsonl [111.3 KB]
sat-en-without-passage.jsonl [229.9 KB]
aqua-rat.jsonl [138.6 KB]
logiqa-en.jsonl [610.8 KB]
logiqa-zh.jsonl [502.3 KB]
gaokao-biology.jsonl [119.3 KB]
LICENSE [5.5 KB]
gaokao-chemistry.jsonl [135.0 KB]
gaokao-mathqa.jsonl [136.4 KB]
lsat-rc.jsonl [974.8 KB]
jec-qa-kd.jsonl [510.4 KB]
gaokao-physics.jsonl [113.4 KB]
lsat-ar.jsonl [226.2 KB]
gaokao-geography.jsonl [113.7 KB]
few_shot_prompts.csv [136.8 KB]
📁 CLUE
📁 OCNLI
dev.json [954.5 KB]
📁 cmnli
📁 cmnli_public
dev.json [2.4 MB]
📁 C3
d-dev.json [794.4 KB]
dev_0.json [794.4 KB]
m-dev.json [1.1 MB]
📁 AFQMC
dev.json [538.5 KB]
test_public.json [538.5 KB]
📁 CMRC
test_public.json [3.1 MB]
dev.json [3.1 MB]
📁 DRCD
dev.json [3.0 MB]
test_public.json [3.0 MB]
📁 piqa
train.jsonl [4.9 MB]
train-labels.lst [31.5 KB]
dev.jsonl [566.9 KB]
dev-labels.lst [3.6 KB]
📁 gsm8k
test.jsonl [732.2 KB]
test_socratic.jsonl [950.2 KB]
train_socratic.jsonl [5.2 MB]
train.jsonl [4.0 MB]
📁 TheoremQA
test.csv [1.5 MB]
📁 math
math.json [4.1 MB]
📁 Xsum
dev.jsonl [25.7 MB]
dev.json [25.7 MB]
dev.csv [25.1 MB]
📁 tydiqa
📁 dev
arabic-dev.jsonl [1.2 MB]
bengali-dev.jsonl [248.2 KB]
indonesian-dev.jsonl [547.9 KB]
korean-dev.jsonl [277.6 KB]
english-dev.jsonl [437.6 KB]
finnish-dev.jsonl [726.5 KB]
telugu-dev.jsonl [1.1 MB]
swahili-dev(1).jsonl [330.4 KB]
swahili-dev.jsonl [330.4 KB]
thai-dev.jsonl [1.4 MB]
russian-dev.jsonl [1.2 MB]
📁 flores_first100
📁 dev
slv_Latn.dev [126.2 KB]
pol_Latn.dev [139.5 KB]
swh_Latn.dev [129.7 KB]
hau_Latn.dev [133.9 KB]
cym_Latn.dev [132.0 KB]
fra_Latn.dev [151.9 KB]
nya_Latn.dev [139.5 KB]
ell_Grek.dev [268.1 KB]
nso_Latn.dev [145.3 KB]
swe_Latn.dev [129.5 KB]
fuv_Latn.dev [119.0 KB]
hye_Armn.dev [252.7 KB]
yor_Latn.dev [158.5 KB]
mkd_Cyrl.dev [233.1 KB]
khm_Khmr.dev [418.2 KB]
por_Latn.dev [137.7 KB]
tam_Taml.dev [390.4 KB]
ceb_Latn.dev [147.7 KB]
mal_Mlym.dev [383.2 KB]
kaz_Cyrl.dev [232.4 KB]
deu_Latn.dev [146.4 KB]
oci_Latn.dev [144.4 KB]
lug_Latn.dev [127.4 KB]
lin_Latn.dev [133.3 KB]
bul_Cyrl.dev [232.7 KB]
xho_Latn.dev [131.7 KB]
asm_Beng.dev [315.3 KB]
azj_Latn.dev [155.7 KB]
glg_Latn.dev [139.8 KB]
tgk_Cyrl.dev [248.7 KB]
nld_Latn.dev [137.0 KB]
zho_Hans.dev [115.5 KB]
wol_Latn.dev [122.6 KB]
ory_Orya.dev [338.7 KB]
heb_Hebr.dev [171.3 KB]
umb_Latn.dev [128.2 KB]
hrv_Latn.dev [125.7 KB]
hun_Latn.dev [142.6 KB]
est_Latn.dev [124.9 KB]
uzn_Latn.dev [139.6 KB]
luo_Latn.dev [129.8 KB]
gle_Latn.dev [152.0 KB]
slk_Latn.dev [135.4 KB]
jav_Latn.dev [128.5 KB]
isl_Latn.dev [135.0 KB]
mya_Mymr.dev [434.3 KB]
ces_Latn.dev [133.8 KB]
ita_Latn.dev [145.7 KB]
ron_Latn.dev [146.4 KB]
som_Latn.dev [140.1 KB]
jpn_Jpan.dev [157.3 KB]
pbt_Arab.dev [209.3 KB]
pan_Guru.dev [319.4 KB]
ltz_Latn.dev [142.4 KB]
tel_Telu.dev [331.9 KB]
gaz_Latn.dev [148.6 KB]
bel_Cyrl.dev [257.4 KB]
eng_Latn.dev [123.3 KB]
tgl_Latn.dev [155.4 KB]
zho_Hant.dev [109.8 KB]
srp_Cyrl.dev [222.1 KB]
ind_Latn.dev [134.3 KB]
dan_Latn.dev [129.9 KB]
khk_Cyrl.dev [237.1 KB]
zsm_Latn.dev [138.7 KB]
kea_Latn.dev [125.6 KB]
ckb_Arab.dev [218.6 KB]
kat_Geor.dev [364.9 KB]
lvs_Latn.dev [138.1 KB]
afr_Latn.dev [132.3 KB]
zul_Latn.dev [138.3 KB]
rus_Cyrl.dev [247.4 KB]
lit_Latn.dev [132.5 KB]
mar_Deva.dev [329.0 KB]
amh_Ethi.dev [214.3 KB]
cat_Latn.dev [138.6 KB]
kam_Latn.dev [125.6 KB]
tur_Latn.dev [137.7 KB]
kan_Knda.dev [350.2 KB]
kor_Hang.dev [148.4 KB]
hin_Deva.dev [315.7 KB]
ibo_Latn.dev [147.2 KB]
lao_Laoo.dev [337.8 KB]
ast_Latn.dev [131.0 KB]
guj_Gujr.dev [308.3 KB]
kir_Cyrl.dev [231.2 KB]
sna_Latn.dev [138.3 KB]
vie_Latn.dev [171.7 KB]
mri_Latn.dev [142.8 KB]
spa_Latn.dev [149.5 KB]
fin_Latn.dev [136.9 KB]
ukr_Cyrl.dev [231.0 KB]
bos_Latn.dev [128.0 KB]
tha_Thai.dev [339.6 KB]
ben_Beng.dev [322.8 KB]
nob_Latn.dev [127.6 KB]
npi_Deva.dev [316.6 KB]
mlt_Latn.dev [142.9 KB]
📁 devtest
nya_Latn.devtest [15.2 KB]
kea_Latn.devtest [13.9 KB]
luo_Latn.devtest [14.6 KB]
srp_Cyrl.devtest [25.4 KB]
ibo_Latn.devtest [16.3 KB]
hau_Latn.devtest [14.7 KB]
vie_Latn.devtest [19.3 KB]
yor_Latn.devtest [17.5 KB]
nld_Latn.devtest [15.6 KB]
kor_Hang.devtest [16.2 KB]
kir_Cyrl.devtest [26.3 KB]
mal_Mlym.devtest [43.2 KB]
zho_Hans.devtest [12.9 KB]
uzn_Latn.devtest [15.9 KB]
zul_Latn.devtest [15.3 KB]
tel_Telu.devtest [36.8 KB]
mlt_Latn.devtest [15.8 KB]
cat_Latn.devtest [16.0 KB]
eng_Latn.devtest [13.8 KB]
zsm_Latn.devtest [15.5 KB]
rus_Cyrl.devtest [27.8 KB]
tam_Taml.devtest [44.1 KB]
mri_Latn.devtest [16.1 KB]
hye_Armn.devtest [29.4 KB]
fra_Latn.devtest [17.2 KB]
fin_Latn.devtest [15.6 KB]
hin_Deva.devtest [35.5 KB]
ltz_Latn.devtest [16.3 KB]
asm_Beng.devtest [35.7 KB]
tgl_Latn.devtest [17.2 KB]
glg_Latn.devtest [15.8 KB]
spa_Latn.devtest [17.0 KB]
azj_Latn.devtest [18.1 KB]
swe_Latn.devtest [14.6 KB]
pan_Guru.devtest [35.3 KB]
lao_Laoo.devtest [38.4 KB]
khm_Khmr.devtest [47.1 KB]
est_Latn.devtest [13.9 KB]
ron_Latn.devtest [16.6 KB]
ell_Grek.devtest [29.9 KB]
nob_Latn.devtest [14.4 KB]
lin_Latn.devtest [15.0 KB]
npi_Deva.devtest [35.5 KB]
tha_Thai.devtest [39.0 KB]
snd_Arab.devtest [21.9 KB]
umb_Latn.devtest [15.3 KB]
wol_Latn.devtest [13.7 KB]
slv_Latn.devtest [14.3 KB]
bel_Cyrl.devtest [29.1 KB]
mya_Mymr.devtest [48.6 KB]
por_Latn.devtest [15.6 KB]
amh_Ethi.devtest [23.0 KB]
deu_Latn.devtest [16.6 KB]
pol_Latn.devtest [15.8 KB]
isl_Latn.devtest [15.2 KB]
lit_Latn.devtest [14.8 KB]
bul_Cyrl.devtest [26.6 KB]
kan_Knda.devtest [38.7 KB]
ita_Latn.devtest [16.8 KB]
tur_Latn.devtest [15.8 KB]
som_Latn.devtest [16.0 KB]
slk_Latn.devtest [14.8 KB]
ckb_Arab.devtest [25.7 KB]
afr_Latn.devtest [15.3 KB]
cym_Latn.devtest [14.5 KB]
sna_Latn.devtest [15.5 KB]
swh_Latn.devtest [14.5 KB]
fuv_Latn.devtest [12.8 KB]
oci_Latn.devtest [16.2 KB]
pbt_Arab.devtest [22.7 KB]
jav_Latn.devtest [14.4 KB]
zho_Hant.devtest [12.3 KB]
kam_Latn.devtest [13.8 KB]
lvs_Latn.devtest [16.0 KB]
tgk_Cyrl.devtest [27.3 KB]
heb_Hebr.devtest [19.1 KB]
ukr_Cyrl.devtest [25.8 KB]
bos_Latn.devtest [14.4 KB]
gaz_Latn.devtest [16.3 KB]
jpn_Jpan.devtest [17.8 KB]
ceb_Latn.devtest [16.6 KB]
xho_Latn.devtest [14.4 KB]
khk_Cyrl.devtest [26.9 KB]
gle_Latn.devtest [16.8 KB]
hun_Latn.devtest [16.6 KB]
nso_Latn.devtest [16.0 KB]
lug_Latn.devtest [14.2 KB]
mkd_Cyrl.devtest [26.8 KB]
ces_Latn.devtest [14.9 KB]
kat_Geor.devtest [41.4 KB]
hrv_Latn.devtest [14.3 KB]
kaz_Cyrl.devtest [26.2 KB]
ben_Beng.devtest [37.0 KB]
ory_Orya.devtest [37.9 KB]
pes_Arab.devtest [23.2 KB]
mar_Deva.devtest [37.8 KB]
ind_Latn.devtest [15.2 KB]
urd_Arab.devtest [24.2 KB]
arb_Arab.devtest [21.8 KB]
guj_Gujr.devtest [35.0 KB]
📁 xstory_cloze
eu_train.jsonl [181.5 KB]
ar_eval.jsonl [908.0 KB]
ru_train.jsonl [251.3 KB]
en_eval.jsonl [706.8 KB]
my_train.jsonl [425.2 KB]
id_train.jsonl [181.4 KB]
te_train.jsonl [340.1 KB]
ar_train.jsonl [220.1 KB]
te_eval.jsonl [1.4 MB]
sw_eval.jsonl [738.8 KB]
zh_eval.jsonl [698.9 KB]
zh_train.jsonl [167.0 KB]
hi_eval.jsonl [1.3 MB]
sw_train.jsonl [177.8 KB]
en_train.jsonl [168.8 KB]
es_train.jsonl [179.1 KB]
my_eval.jsonl [1.8 MB]
es_eval.jsonl [749.0 KB]
eu_eval.jsonl [750.7 KB]
ru_eval.jsonl [1.0 MB]
hi_train.jsonl [324.2 KB]
id_eval.jsonl [759.1 KB]
📁 race
📁 validation
middle.jsonl [1.8 MB]
high.jsonl [6.8 MB]
📁 test
high.jsonl [6.9 MB]
middle.jsonl [1.8 MB]
📁 ceval
📁 formal_ceval
📁 dev
metrology_engineer_dev.csv [2.4 KB]
logic_dev.csv [5.5 KB]
advanced_mathematics_dev.csv [6.8 KB]
environmental_impact_assessment_engineer_dev.csv [2.4 KB]
high_school_geography_dev.csv [2.0 KB]
basic_medicine_dev.csv [1.7 KB]
middle_school_mathematics_dev.csv [3.1 KB]
high_school_biology_dev.csv [2.1 KB]
chinese_language_and_literature_dev.csv [1.8 KB]
high_school_chinese_dev.csv [5.1 KB]
high_school_physics_dev.csv [2.2 KB]
discrete_mathematics_dev.csv [1.9 KB]
middle_school_geography_dev.csv [2.0 KB]
middle_school_biology_dev.csv [4.2 KB]
high_school_mathematics_dev.csv [3.4 KB]
accountant_dev.csv [3.3 KB]
college_economics_dev.csv [3.5 KB]
high_school_politics_dev.csv [4.6 KB]
plant_protection_dev.csv [3.6 KB]
teacher_qualification_dev.csv [3.1 KB]
sports_science_dev.csv [4.0 KB]
physician_dev.csv [1.9 KB]
college_chemistry_dev.csv [3.5 KB]
college_programming_dev.csv [2.8 KB]
civil_servant_dev.csv [4.4 KB]
middle_school_chemistry_dev.csv [3.7 KB]
marxism_dev.csv [2.0 KB]
computer_architecture_dev.csv [2.7 KB]
computer_network_dev.csv [2.2 KB]
probability_and_statistics_dev.csv [6.6 KB]
law_dev.csv [4.0 KB]
education_science_dev.csv [3.0 KB]
high_school_chemistry_dev.csv [2.5 KB]
electrical_engineer_dev.csv [2.1 KB]
urban_and_rural_planner_dev.csv [3.0 KB]
business_administration_dev.csv [3.0 KB]
fire_engineer_dev.csv [2.1 KB]
middle_school_physics_dev.csv [3.4 KB]
middle_school_history_dev.csv [1.9 KB]
professional_tour_guide_dev.csv [1.7 KB]
veterinary_medicine_dev.csv [2.2 KB]
college_physics_dev.csv [3.7 KB]
clinical_medicine_dev.csv [1.8 KB]
modern_chinese_history_dev.csv [2.8 KB]
legal_professional_dev.csv [6.8 KB]
ideological_and_moral_cultivation_dev.csv [1.2 KB]
high_school_history_dev.csv [2.3 KB]
art_studies_dev.csv [1.3 KB]
mao_zedong_thought_dev.csv [3.2 KB]
operating_system_dev.csv [2.4 KB]
tax_accountant_dev.csv [4.1 KB]
middle_school_politics_dev.csv [3.5 KB]
📁 test
teacher_qualification_test.csv [96.4 KB]
discrete_mathematics_test.csv [32.0 KB]
high_school_history_test.csv [51.0 KB]
metrology_engineer_test.csv [41.6 KB]
civil_servant_test.csv [167.9 KB]
art_studies_test.csv [33.8 KB]
environmental_impact_assessment_engineer_test.csv [76.6 KB]
education_science_test.csv [48.6 KB]
middle_school_biology_test.csv [42.0 KB]
electrical_engineer_test.csv [64.6 KB]
clinical_medicine_test.csv [36.8 KB]
mao_zedong_thought_test.csv [50.6 KB]
veterinary_medicine_test.csv [34.0 KB]
physician_test.csv [78.1 KB]
fire_engineer_test.csv [75.5 KB]
college_programming_test.csv [74.8 KB]
high_school_mathematics_test.csv [36.9 KB]
computer_network_test.csv [30.8 KB]
logic_test.csv [136.1 KB]
high_school_biology_test.csv [50.2 KB]
middle_school_history_test.csv [41.5 KB]
middle_school_chemistry_test.csv [42.4 KB]
college_chemistry_test.csv [40.0 KB]
probability_and_statistics_test.csv [52.3 KB]
middle_school_physics_test.csv [43.7 KB]
high_school_politics_test.csv [77.7 KB]
law_test.csv [73.1 KB]
middle_school_geography_test.csv [20.4 KB]
tax_accountant_test.csv [160.8 KB]
basic_medicine_test.csv [24.3 KB]
middle_school_mathematics_test.csv [28.6 KB]
urban_and_rural_planner_test.csv [98.7 KB]
operating_system_test.csv [26.5 KB]
sports_science_test.csv [27.8 KB]
computer_architecture_test.csv [35.4 KB]
accountant_test.csv [163.2 KB]
marxism_test.csv [33.8 KB]
modern_chinese_history_test.csv [45.4 KB]
advanced_mathematics_test.csv [45.2 KB]
business_administration_test.csv [70.0 KB]
high_school_geography_test.csv [36.4 KB]
high_school_chinese_test.csv [104.0 KB]
legal_professional_test.csv [114.4 KB]
college_physics_test.csv [50.6 KB]
high_school_chemistry_test.csv [42.1 KB]
professional_tour_guide_test.csv [34.5 KB]
college_economics_test.csv [106.2 KB]
middle_school_politics_test.csv [66.7 KB]
chinese_language_and_literature_test.csv [27.0 KB]
high_school_physics_test.csv [56.5 KB]
ideological_and_moral_cultivation_test.csv [30.7 KB]
plant_protection_test.csv [26.8 KB]
📁 val
logic_val.csv [14.7 KB]
probability_and_statistics_val.csv [5.3 KB]
professional_tour_guide_val.csv [3.8 KB]
discrete_mathematics_val.csv [3.0 KB]
college_programming_val.csv [8.6 KB]
high_school_mathematics_val.csv [4.7 KB]
computer_network_val.csv [3.3 KB]
middle_school_history_val.csv [5.4 KB]
mao_zedong_thought_val.csv [4.9 KB]
civil_servant_val.csv [19.8 KB]
college_physics_val.csv [5.6 KB]
ideological_and_moral_cultivation_val.csv [2.8 KB]
ceval_contamination_annotations.json [85.4 KB]
environmental_impact_assessment_engineer_val.csv [8.3 KB]
middle_school_physics_val.csv [4.8 KB]
high_school_politics_val.csv [8.3 KB]
physician_val.csv [7.5 KB]
middle_school_mathematics_val.csv [4.4 KB]
basic_medicine_val.csv [2.2 KB]
high_school_history_val.csv [6.1 KB]
college_chemistry_val.csv [3.9 KB]
law_val.csv [7.4 KB]
accountant_val.csv [18.1 KB]
plant_protection_val.csv [3.1 KB]
legal_professional_val.csv [11.5 KB]
electrical_engineer_val.csv [7.3 KB]
high_school_geography_val.csv [3.5 KB]
business_administration_val.csv [8.3 KB]
college_economics_val.csv [13.0 KB]
operating_system_val.csv [2.8 KB]
fire_engineer_val.csv [9.1 KB]
metrology_engineer_val.csv [5.5 KB]
sports_science_val.csv [3.0 KB]
high_school_chemistry_val.csv [5.1 KB]
education_science_val.csv [4.8 KB]
middle_school_politics_val.csv [6.7 KB]
middle_school_chemistry_val.csv [5.1 KB]
chinese_language_and_literature_val.csv [2.9 KB]
high_school_physics_val.csv [6.7 KB]
high_school_chinese_val.csv [9.9 KB]
veterinary_medicine_val.csv [4.0 KB]
teacher_qualification_val.csv [11.0 KB]
art_studies_val.csv [3.8 KB]
clinical_medicine_val.csv [3.6 KB]
middle_school_geography_val.csv [2.3 KB]
computer_architecture_val.csv [3.6 KB]
marxism_val.csv [3.8 KB]
tax_accountant_val.csv [17.5 KB]
modern_chinese_history_val.csv [4.6 KB]
high_school_biology_val.csv [5.6 KB]
advanced_mathematics_val.csv [4.8 KB]
urban_and_rural_planner_val.csv [11.5 KB]
middle_school_biology_val.csv [4.7 KB]
📁 mbpp
mbpp.jsonl [550.5 KB]
sanitized-mbpp.jsonl [248.7 KB]
📁 SuperGLUE
📁 COPA
test.jsonl [80.8 KB]
val.jsonl [17.7 KB]
📁 CB
val.jsonl [24.0 KB]
test.jsonl [97.5 KB]
📁 ReCoRD
test.jsonl [13.0 MB]
val.jsonl [14.5 MB]
📁 RTE
val.jsonl [102.4 KB]
📁 WiC
test.jsonl [292.1 KB]
val.jsonl [144.1 KB]
📁 AX-g
AX-g.jsonl [73.2 KB]
📁 AX-b
AX-b.jsonl [346.0 KB]
📁 MultiRC
val.jsonl [537.2 KB]
test.jsonl [960.8 KB]
📁 WSC
test.jsonl [41.7 KB]
val.jsonl [30.6 KB]
📁 BoolQ
test.jsonl [2.1 MB]
val.jsonl [2.2 MB]
📁 drop
drop_dataset_dev.json [13.1 MB]
drop_dataset_train.json [51.5 MB]
license.txt [20.1 KB]
📁 summedits
summedits.jsonl [26.7 MB]
📁 lambada
test.jsonl [1.8 MB]
📁 triviaqa
triviaqa-train.jsonl [7.2 MB]
triviaqa-validation.jsonl [3.2 MB]
trivia-dev.qa.csv [3.0 MB]
trivia-test.qa.csv [3.9 MB]
📁 openbookqa
📁 Main
train.jsonl [1.4 MB]
test.tsv [143.4 KB]
train.tsv [1.4 MB]
openbook.txt [74.1 KB]
dev.tsv [150.6 KB]
dev.jsonl [153.3 KB]
test.jsonl [149.7 KB]
📁 Additional
train_complete.jsonl [2.1 MB]
test_complete.jsonl [218.0 KB]
dev_complete.jsonl [223.1 KB]
crowdsourced-facts.txt [196.8 KB]
📁 GAOKAO-BENCH
📁 data
📁 Multiple-choice_Questions
2010-2022_Chinese_Modern_Lit.json [210.3 KB]
2010-2022_Political_Science_MCQs.json [463.2 KB]
2010-2022_Physics_MCQs.json [89.7 KB]
2010-2022_Math_II_MCQs.json [173.3 KB]
2010-2022_Math_I_MCQs.json [198.6 KB]
2010-2022_Geography_MCQs.json [74.8 KB]
2010-2022_English_Fill_in_Blanks.json [255.7 KB]
2010-2022_Chemistry_MCQs.json [207.4 KB]
2010-2022_Chinese_Lang_and_Usage_MCQs.json [131.8 KB]
2010-2022_English_Reading_Comp.json [521.9 KB]
2010-2022_History_MCQs.json [342.6 KB]
2010-2022_Biology_MCQs.json [180.5 KB]
2012-2022_English_Cloze_Test.json [107.0 KB]
2010-2013_English_MCQs.json [76.2 KB]
📁 Open-ended_Questions
2010-2022_Chinese_Language_Literary_Text_Reading.json [299.5 KB]
2010-2022_Math_II_Open-ended_Questions.json [262.1 KB]
2010-2022_Geography_Open-ended_Questions.json [43.5 KB]
2010-2022_Chemistry_Open-ended_Questions.json [51.1 KB]
2010-2022_Chinese_Language_Practical_Text_Reading.json [211.8 KB]
2010-2022_Chinese_Language_Classical_Chinese_Reading.json [208.4 KB]
2010-2022_Political_Science_Open-ended_Questions.json [253.5 KB]
2010-2022_Chinese_Language_Language_and_Writing_Skills_Open-ended_Questions.json [85.8 KB]
2010-2022_Physics_Open-ended_Questions.json [79.4 KB]
2012-2022_English_Language_Error_Correction.json [84.0 KB]
2010-2022_History_Open-ended_Questions.json [380.9 KB]
2010-2022_Math_I_Open-ended_Questions.json [300.0 KB]
2010-2022_Biology_Open-ended_Questions.json [267.2 KB]
2010-2022_Chinese_Language_Ancient_Poetry_Reading.json [78.0 KB]
📁 Fill-in-the-blank_Questions
2010-2022_Math_II_Fill-in-the-Blank.json [65.3 KB]
2014-2022_English_Language_Cloze_Passage.json [92.6 KB]
2010-2022_Math_I_Fill-in-the-Blank.json [69.7 KB]
2010-2022_Chinese_Language_Famous_Passages_and_Sentences_Dictation.json [28.7 KB]
【录播】OpenCompass大模型评估.mp4 [850.4 MB]
OpenCompassData-core-20240207.zip [148.9 MB]
【课件】OpenCompass模型评估.pdf [490.0 KB]
【资料】OpenCompass模型评估.pdf [197.9 KB]
📁 day26_基于本地大模型的AI试题系统（方案篇）
📁 数据
2020年高考生物选择题专项训练20套附答案及解析.docx [454.6 KB]
2020年高考生物选择题专项训练11-15套Word版含答案及解析.docx [42.0 KB]
高考生物常识选择题单选题100道及答案.docx [27.3 KB]
数据示例.xls [19.5 KB]
2022年高考生物选择题专项训练(共6份).docx [2.5 MB]
2023年高考生物选择题专练(8套)含答案及解析.docx [37.5 KB]
【录播】基于本地大模型的AI试题系统（方案篇）.mp4 [1.3 GB]
AI题库项目分析.png [245.3 KB]
📁 day06_自定义vocab
📁 demo_6
📁 model
📁 bert-base-chinese
📁 .locks
📁 models--bert-base-chinese
📁 models--bert-base-chinese
📁 snapshots
📁 c30a6ed22ab4564dc1e3b2ecbf6e766b0611a33f
tokenizer.json [262.6 KB]
tokenizer_config.json [49.0 B]
config.json [624.0 B]
model.safetensors [392.5 MB]
vocab.txt [107.0 KB]
📁 .no_exist
📁 c30a6ed22ab4564dc1e3b2ecbf6e766b0611a33f
special_tokens_map.json
added_tokens.json
📁 refs
main [40.0 B]
📁 blobs_20241231_024804
📁 __pycache__
MyData.cpython-312.pyc [1.5 KB]
net.cpython-312.pyc [1.7 KB]
📁 .idea
📁 inspectionProfiles
profiles_settings.xml [174.0 B]
modules.xml [271.0 B]
encodings.xml [290.0 B]
.gitignore [50.0 B]
workspace.xml [7.7 KB]
misc.xml [189.0 B]
demo_6.iml [291.0 B]
📁 params
1_bert.pth [7.5 KB]
0_bert.pth [7.5 KB]
3_bert.pth [7.5 KB]
2_bert.pth [7.5 KB]
📁 data
📁 Weibo
train.csv [4.0 MB]
dataset_info.json [2.3 KB]
📁 ChnSentiCorp
📁 train
cache-b85c50cd434dd865.arrow [73.5 KB]
cache-1e3bba9512e20e17.arrow [73.5 KB]
cache-3432ecc2b0d45f4c.arrow [73.5 KB]
cache-3bdb9443d1ca0706.arrow [624.0 B]
cache-60739da7e9e626bf.arrow [73.5 KB]
cache-980049a695f6628c.arrow [69.1 KB]
cache-eb31b953e8e788fb.arrow [73.5 KB]
cache-703908ea6da8e823.arrow [73.5 KB]
cache-badcf79eb9fa62a0.arrow [73.5 KB]
cache-a41fe1013beb0d46.arrow [73.5 KB]
cache-618b312c42069194.arrow [73.5 KB]
cache-b4e51936648802e2.arrow [76.7 KB]
cache-c5b262546ff026fd.arrow [76.7 KB]
cache-a6ab41ffbc1946d5.arrow [8.0 KB]
cache-942e97a8804ee679.arrow [73.5 KB]
cache-39dfc0aff9c238ae.arrow [73.5 KB]
cache-8a97cd1e06b735d2.arrow [73.5 KB]
cache-7f783dce092dc384.arrow [73.5 KB]
cache-9f44d179cc25c59e.arrow [73.5 KB]
cache-fdafe12f59ab3430.arrow [73.5 KB]
cache-d7c6377d856b0538.arrow [73.5 KB]
dataset.arrow [3.0 MB]
cache-a34d90b946dc58b8.arrow [73.5 KB]
cache-b53b61aef9d859aa.arrow [73.5 KB]
cache-42a7d570466d6993.arrow [76.7 KB]
dataset_info.json [1.8 KB]
state.json [256.0 B]
📁 test
state.json [255.0 B]
dataset_info.json [1.8 KB]
dataset.arrow [372.3 KB]
cache-7dd332715d90b654.arrow [10.0 KB]
📁 validation
cache-428974171b74f1a0.arrow [9.6 KB]
cache-585e054403b710b3.arrow [9.6 KB]
dataset.arrow [376.6 KB]
cache-749efdb8f0ee42be.arrow [9.6 KB]
cache-805d054a96ccc48f.arrow [9.6 KB]
cache-a1c8a8bb0a669e93.arrow [9.6 KB]
cache-486e66fea9239c3f.arrow [9.6 KB]
cache-800047dd8fdede53.arrow [9.6 KB]
cache-85b0ee5d0aeacbe5.arrow [9.6 KB]
state.json [261.0 B]
cache-8ae76a3b52248a8f.arrow [9.6 KB]
cache-4a46afc6455cc3f0.arrow [9.6 KB]
cache-5cd00431b9d3a916.arrow [9.6 KB]
cache-1b273238fdadead7.arrow [9.6 KB]
cache-e621cb96adf0c923.arrow [10.0 KB]
cache-9b7789b1e0e636fb.arrow [9.6 KB]
cache-c072f719f0b9b62a.arrow [9.6 KB]
dataset_info.json [1.8 KB]
dataset_dict.json [43.0 B]
MyData.py [856.0 B]
token_test.py [1.5 KB]
train.py [4.3 KB]
vocab_test.py [1.1 KB]
data_test.py [665.0 B]
test.py [2.1 KB]
net.py [989.0 B]
run.py [1.7 KB]
MyData02.py [589.0 B]
【录播】自定义vocab.mp4 [921.7 MB]
【课件】Hugging Face 模型微调训练（自定义vocab）.pdf [509.3 KB]
📁 day05_基于 BERT 的中文评价情感分析
📁 demo_5
📁 .idea
📁 inspectionProfiles
profiles_settings.xml [174.0 B]
workspace.xml [7.2 KB]
modules.xml [271.0 B]
demo_5.iml [291.0 B]
.gitignore [50.0 B]
misc.xml [189.0 B]
📁 params
1_bert.pth [7.5 KB]
0_bert.pth [7.5 KB]
2_bert.pth [7.5 KB]
📁 data
📁 ChnSentiCorp
📁 train
cache-b53b61aef9d859aa.arrow [73.5 KB]
dataset.arrow [3.0 MB]
cache-3432ecc2b0d45f4c.arrow [73.5 KB]
cache-fdafe12f59ab3430.arrow [73.5 KB]
cache-c5b262546ff026fd.arrow [76.7 KB]
cache-60739da7e9e626bf.arrow [73.5 KB]
cache-a34d90b946dc58b8.arrow [73.5 KB]
cache-b4e51936648802e2.arrow [76.7 KB]
cache-badcf79eb9fa62a0.arrow [73.5 KB]
cache-b85c50cd434dd865.arrow [73.5 KB]
cache-3bdb9443d1ca0706.arrow [624.0 B]
cache-8a97cd1e06b735d2.arrow [73.5 KB]
cache-39dfc0aff9c238ae.arrow [73.5 KB]
cache-7f783dce092dc384.arrow [73.5 KB]
cache-a6ab41ffbc1946d5.arrow [8.0 KB]
state.json [256.0 B]
cache-a41fe1013beb0d46.arrow [73.5 KB]
cache-703908ea6da8e823.arrow [73.5 KB]
cache-42a7d570466d6993.arrow [76.7 KB]
cache-1e3bba9512e20e17.arrow [73.5 KB]
cache-9f44d179cc25c59e.arrow [73.5 KB]
cache-942e97a8804ee679.arrow [73.5 KB]
cache-618b312c42069194.arrow [73.5 KB]
cache-980049a695f6628c.arrow [69.1 KB]
dataset_info.json [1.8 KB]
cache-eb31b953e8e788fb.arrow [73.5 KB]
cache-d7c6377d856b0538.arrow [73.5 KB]
📁 test
dataset.arrow [372.3 KB]
dataset_info.json [1.8 KB]
cache-7dd332715d90b654.arrow [10.0 KB]
state.json [255.0 B]
📁 validation
cache-1b273238fdadead7.arrow [9.6 KB]
cache-4a46afc6455cc3f0.arrow [9.6 KB]
cache-800047dd8fdede53.arrow [9.6 KB]
cache-585e054403b710b3.arrow [9.6 KB]
dataset.arrow [376.6 KB]
cache-749efdb8f0ee42be.arrow [9.6 KB]
cache-805d054a96ccc48f.arrow [9.6 KB]
cache-5cd00431b9d3a916.arrow [9.6 KB]
cache-486e66fea9239c3f.arrow [9.6 KB]
cache-a1c8a8bb0a669e93.arrow [9.6 KB]
cache-e621cb96adf0c923.arrow [10.0 KB]
cache-428974171b74f1a0.arrow [9.6 KB]
cache-9b7789b1e0e636fb.arrow [9.6 KB]
cache-85b0ee5d0aeacbe5.arrow [9.6 KB]
cache-c072f719f0b9b62a.arrow [9.6 KB]
state.json [261.0 B]
cache-8ae76a3b52248a8f.arrow [9.6 KB]
dataset_info.json [1.8 KB]
dataset_dict.json [43.0 B]
hermes-function-calling-v1.csv [14.7 MB]
📁 __pycache__
MyData.cpython-312.pyc [1.5 KB]
net.cpython-312.pyc [1.7 KB]
📁 model
📁 bert-base-chinese
📁 .locks
📁 models--bert-base-chinese
📁 models--bert-base-chinese
📁 blobs
📁 .no_exist
📁 c30a6ed22ab4564dc1e3b2ecbf6e766b0611a33f
special_tokens_map.json
added_tokens.json
📁 snapshots
📁 c30a6ed22ab4564dc1e3b2ecbf6e766b0611a33f
tokenizer_config.json [49.0 B]
vocab.txt [107.0 KB]
tokenizer.json [262.6 KB]
model.safetensors [392.5 MB]
config.json [624.0 B]
📁 refs
main [40.0 B]
data_test.py [658.0 B]
run.py [1.7 KB]
MyData.py [856.0 B]
net.py [989.0 B]
train.py [2.6 KB]
token_test.py [1.5 KB]
【资料】Hugging Face 模型微调训练（基于 BERT 的中文评价情感分析）.pdf [304.7 KB]
【录播】基于 BERT 的中文评价情感分析.mp4 [754.7 MB]
【课件】Hugging Face 模型微调训练（基于 BERT 的中文评价情感分析）.pdf [500.6 KB]
📁 day11_Llama3.2模型微调
📁 demo_11
📁 .idea
📁 inspectionProfiles
profiles_settings.xml [174.0 B]
misc.xml [168.0 B]
.gitignore [50.0 B]
demo_11.iml [325.0 B]
modules.xml [273.0 B]
workspace.xml [2.0 KB]
test02.py [1.1 KB]
test01.py [336.0 B]
【录播】llama3.2模型微调.mp4 [865.3 MB]
data.zip [280.1 KB]
【资料】LLaMa3微调（使用 LLaMA-Factory 微调 LLaMA3）.pdf [140.9 KB]
【课件】LLaMa3微调（使用 LLaMA-Factory 微调 LLaMA3）.pdf [602.0 KB]
📁 day18_LMDeploy部署大模型
📁 demo_18
test01.py [457.0 B]
test02.py [440.0 B]
【录播】LMDeploy部署大模型.mp4 [952.8 MB]
【资料】LMDeploy部署大模型.pdf [327.0 KB]
📁 day16_Qwen模型打包部署（HF转GGUF&ollama+open_webui部署）
【资料】Qwen模型打包部署（Lora模型合并&转GGUF模型部署）.pdf [395.7 KB]
【录播】Qwen模型打包部署（HF转GGUF&ollama+open_webui部署）.mp4 [848.7 MB]
Qwen1___5-1___8B-Chat-merged-q8.gguf [1.8 GB]
【课件】Qwen模型打包部署（Lora模型合并&转GGUF模型部署）.pdf [555.3 KB]
📁 day23_AutoGen_Studio搭建多智能体应用
📁 图像资料
Agent02.png [113.4 KB]
Agent01.png [121.1 KB]
Agent03.png [31.7 KB]
【资料】AutoGen_Studio搭建多智能体应用.pdf [859.3 KB]
【课件】AutoGen_Studio搭建多智能体应用.pdf [599.8 KB]
【录播】AutoGen_Studio搭建多智能体应用.mp4 [753.1 MB]
📁 day14_LLaMA-Factory模型评估与QLora微调
【录播】LLama-Factory模型评估与QLora微调.mp4 [763.6 MB]
【资料】LLama-Factory模型评估.pdf [295.4 KB]
【课件】LLama-Factory模型评估与QLora微调.pdf [512.7 KB]
AI技术路线.pdf [107.4 KB]
📁 day30_基于pytorch的语音唤醒系统
📁 项目源码
📁 wakeup_test
📁 __pycache__
dataset.cpython-312.pyc [4.8 KB]
audio_processor.cpython-312.pyc [3.9 KB]
crnn.cpython-312.pyc [2.5 KB]
📁 checkpoints
best_model.pth [3.5 MB]
📁 results
errors.txt
confusion_matrix.png [15.9 KB]
📁 .idea
📁 inspectionProfiles
profiles_settings.xml [174.0 B]
wakeup_test.iml [291.0 B]
modules.xml [281.0 B]
.gitignore [50.0 B]
misc.xml [189.0 B]
workspace.xml [6.4 KB]
📁 dataset
📁 train
📁 not_wake
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📁 wake
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📁 split_dataset
📁 val
📁 wake
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📁 not_wake
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📁 train
📁 wake
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📁 not_wake
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test.py [2.2 KB]
train.py [4.2 KB]
get_voice.py [2.0 KB]
crnn.py [1.5 KB]
dataset.py [3.3 KB]
realtime_test.py [3.4 KB]
audio_processor.py [2.5 KB]
data_splite.py [1.4 KB]
语音唤醒.png [171.2 KB]
【课件】扩展项目（基于pytorch实现的语音识别）.pdf [487.9 KB]
【录播】扩展项目（基于pytorch的语音唤醒系统）.mp4 [1.7 GB]
📁 day21_llama-index入门实操
📁 demo_21
📁 data
README_zh-CN.md [14.5 KB]
download_hf.py [177.0 B]
test03.py [746.0 B]
test02.py [1.6 KB]
test01.py [534.0 B]
【录播】Llama_index入门实操.mp4 [934.0 MB]
【课件】Llama_index入门实操.pdf [496.1 KB]
📁 day09_远程GPU服务器
📁 代码与资料
📁 GPT2训练日志及权重
output.log [1.3 MB]
net.pt [389.4 MB]
📁 模型推理代码
detect.py [724.0 B]
detect02.py [4.5 KB]
GPU服务器配置与使用.pdf [697.1 KB]
1月8日.mp4 [749.4 MB]
未命名文档.PanD [93.0 B]
📁 day17_Xtuner微调大模型
📁 xtuner数据集转换代码
📁 data
target_data.json [714.2 KB]
ruozhiba_qaswift.json [588.5 KB]
data_utils.py [742.0 B]
📁 xtuner微调配置文件
qwen1_5_1_8b_chat_qlora_alpaca_e3.py [7.6 KB]
【资料】xtuner微调大模型教程.pdf [184.9 KB]
【录播】Xtuner微调大模型（QLora与Lora）.mp4 [923.5 MB]
📁 day07_如何处理超长文本训练问题
📁 demo_7
📁 data
📁 news
test.csv [24.1 MB]
train.csv [120.2 MB]
validation.csv [12.2 MB]
news_data_info.json [1.8 KB]
📁 Weibo
dataset_info.json [2.3 KB]
train.csv [4.0 MB]
new_test.csv [18.3 KB]
data_test02.py [915.0 B]
train.py [4.3 KB]
data_test.py [300.0 B]
net.py [1.3 KB]
validation.csv [18.4 KB]
MyData.py [581.0 B]
data.py [171.0 B]
【录播】如何处理超长文本训练问题.mp4 [754.4 MB]
【课件】Hugging Face 模型微调训练（如何处理超长文本训练问题）.pdf [511.4 KB]
model.zip [364.5 MB]
📁 day20_llama-index核心组件
📁 demo_20
📁 data
README_zh-CN.md [14.5 KB]
pdf内容研报.pdf [189.1 KB]
requirements.txt [4.3 KB]
test02.py [222.0 B]
test01.py [365.0 B]
模型微调与RAG.png [104.6 KB]
【资料】Llama_Index（核心组件介绍）.pdf [624.0 KB]
【课件】Llama_Index（核心组件介绍）.pdf [486.3 KB]
【录播】Llama_Index核心组件介绍.mp4 [1.2 GB]
📁 3_LangChain
📁 LangChain
📁 serve
joke_server.py [573.0 B]
joke_client.py [136.0 B]
📁 assets
data_connection.jpg [42.3 KB]
langchain.png [54.6 KB]
model_io.jpg [643.3 KB]
memory.db [8.0 KB]
index.ipynb [63.7 KB]
llama2.pdf [276.7 KB]
example_prompt_template.txt [31.0 B]
LangChain.mp4 [618.5 MB]
📁 day25_deep-seek与多卡训练
📁 课堂笔记
deepseek.png [152.9 KB]
【录播】deep_seek与多卡训练.mp4 [1.0 GB]
【课件】deepseek与分布式训练.pdf [491.8 KB]
📁 day10_llama3大模型本地调用
📁 demo_10
📁 Llama3_test
test01.py [165.0 B]
test02.py [1.2 KB]
detect02.py [4.5 KB]
data.py [501.0 B]
train.py [3.2 KB]
detect.py [709.0 B]
net.pt [389.4 MB]
【课件】llama3大模型本地调用.pdf [555.9 KB]
【录播】llama3大模型本地调用.mp4 [912.7 MB]
📁 day15_Qwen模型打包部署（Lora模型合并&转GGUF模型部署）
📁 Lora
📁 checkpoint-400
scheduler.pt [1.0 KB]
adapter_config.json [744.0 B]
rng_state.pth [13.9 KB]
tokenizer.json [10.9 MB]
training_args.bin [5.6 KB]
tokenizer_config.json [1.3 KB]
adapter_model.safetensors [228.8 MB]
vocab.json [2.6 MB]
added_tokens.json [80.0 B]
trainer_state.json [15.1 KB]
merges.txt [1.6 MB]
optimizer.pt [457.8 MB]
special_tokens_map.json [367.0 B]
README.md [5.0 KB]
【录播】HF模型转GGUF以及使用ollama部署.mp4 [1.1 GB]
【资料】Qwen模型打包部署（Lora模型合并&转GGUF模型部署）.pdf [395.7 KB]
【课件】Qwen模型打包部署（Lora模型合并&转GGUF模型部署）.pdf [555.3 KB]
📁 day28_基于RAG的法律条文智能助手（方案篇）
📁 llama_factory对话模板导出
文件位置.jpg [19.6 KB]
mytest.py [829.0 B]
📁 模型微调数据集
train_data.json [20.1 KB]
📁 RAG知识库数据获取
data_test01.py [1.6 KB]
data_test02.py [1.6 KB]
【录播】基于RAG的法律条文智能助手【方案篇】.mp4 [1.1 GB]
【课件】基于RAG的法律条文智能助手（方案篇）.pdf [495.8 KB]
RAG项目需求.png [125.3 KB]
R1思维链与微调.png [109.1 KB]
📁 day04_Hugging Face 核心组件介绍
📁 demo_4
📁 trasnFormers_test
📁 model
📁 bert-base-chinese
📁 models--bert-base-chinese
📁 snapshots
📁 c30a6ed22ab4564dc1e3b2ecbf6e766b0611a33f
vocab.txt [107.0 KB]
config.json [624.0 B]
tokenizer_config.json [49.0 B]
model.safetensors [392.5 MB]
tokenizer.json [262.6 KB]
📁 refs
main [40.0 B]
📁 .no_exist
📁 c30a6ed22ab4564dc1e3b2ecbf6e766b0611a33f
added_tokens.json
special_tokens_map.json
📁 blobs
📁 .locks
📁 models--bert-base-chinese
📁 uer
📁 gpt2-chinese-cluecorpussmall
📁 .locks
📁 models--uer--gpt2-chinese-cluecorpussmall
📁 models--uer--gpt2-chinese-cluecorpussmall
📁 snapshots
📁 blobs
📁 .no_exist
📁 refs
main [40.0 B]
test03.py [658.0 B]
test01.py [489.0 B]
test02.py [2.7 KB]
📁 API_test
api_test02.py [361.0 B]
api_test01.py [243.0 B]
📁 dataset
dataset_test.py [425.0 B]
📁 data
📁 ChnSentiCorp
📁 test
state.json [255.0 B]
dataset.arrow [372.3 KB]
cache-7dd332715d90b654.arrow [10.0 KB]
dataset_info.json [1.8 KB]
📁 validation
cache-9b7789b1e0e636fb.arrow [9.6 KB]
state.json [261.0 B]
cache-805d054a96ccc48f.arrow [9.6 KB]
dataset_info.json [1.8 KB]
cache-585e054403b710b3.arrow [9.6 KB]
cache-85b0ee5d0aeacbe5.arrow [9.6 KB]
cache-749efdb8f0ee42be.arrow [9.6 KB]
cache-1b273238fdadead7.arrow [9.6 KB]
cache-8ae76a3b52248a8f.arrow [9.6 KB]
cache-a1c8a8bb0a669e93.arrow [9.6 KB]
cache-5cd00431b9d3a916.arrow [9.6 KB]
cache-e621cb96adf0c923.arrow [10.0 KB]
cache-c072f719f0b9b62a.arrow [9.6 KB]
cache-428974171b74f1a0.arrow [9.6 KB]
cache-4a46afc6455cc3f0.arrow [9.6 KB]
cache-800047dd8fdede53.arrow [9.6 KB]
dataset.arrow [376.6 KB]
cache-486e66fea9239c3f.arrow [9.6 KB]
📁 train
cache-badcf79eb9fa62a0.arrow [73.5 KB]
state.json [256.0 B]
cache-a41fe1013beb0d46.arrow [73.5 KB]
dataset_info.json [1.8 KB]
cache-1e3bba9512e20e17.arrow [73.5 KB]
cache-b53b61aef9d859aa.arrow [73.5 KB]
cache-eb31b953e8e788fb.arrow [73.5 KB]
cache-b85c50cd434dd865.arrow [73.5 KB]
cache-b4e51936648802e2.arrow [76.7 KB]
cache-8a97cd1e06b735d2.arrow [73.5 KB]
cache-7f783dce092dc384.arrow [73.5 KB]
cache-9f44d179cc25c59e.arrow [73.5 KB]
cache-3432ecc2b0d45f4c.arrow [73.5 KB]
cache-a34d90b946dc58b8.arrow [73.5 KB]
cache-703908ea6da8e823.arrow [73.5 KB]
cache-980049a695f6628c.arrow [69.1 KB]
cache-fdafe12f59ab3430.arrow [73.5 KB]
cache-a6ab41ffbc1946d5.arrow [8.0 KB]
cache-60739da7e9e626bf.arrow [73.5 KB]
cache-942e97a8804ee679.arrow [73.5 KB]
cache-3bdb9443d1ca0706.arrow [624.0 B]
cache-618b312c42069194.arrow [73.5 KB]
cache-d7c6377d856b0538.arrow [73.5 KB]
cache-39dfc0aff9c238ae.arrow [73.5 KB]
dataset.arrow [3.0 MB]
cache-c5b262546ff026fd.arrow [76.7 KB]
cache-42a7d570466d6993.arrow [76.7 KB]
dataset_dict.json [43.0 B]
hermes-function-calling-v1.csv [14.7 MB]
【资料】Hugging Face 核心组件介绍.pdf [243.1 KB]
【课件】Hugging Face 核心组件介绍.pdf [501.5 KB]
【录播】Hugging Face 核心组件介绍.mp4 [762.9 MB]
📁 2_RAG-Embedding-Vector
📁 day01
📁 RAG-Embeddings
📁 assets
rag.png [81.7 KB]
vector.png [23.6 KB]
vectordb.png [16.6 KB]
GraphRAG.png [752.8 KB]
mteb.png [23.6 KB]
sbert.png [20.8 KB]
embeddings.png [48.8 KB]
sbert-rerank.png [71.8 KB]
sim.png [26.8 KB]
RAG.mp4 [1.9 MB]
table_rag.png [420.4 KB]
llama2_page8.pdf [176.4 KB]
.env [80.0 B]
llama2.pdf [276.7 KB]
index.ipynb [56.2 KB]
chinese_utils.py [979.0 B]
rank.py [3.1 KB]
Python语法入门教程.md [49.3 KB]
RAG搭建流程和文本向量.mp4 [469.0 MB]
📁 day02
📁 RAG-Embeddings
📁 assets
vector.png [23.6 KB]
mteb.png [23.6 KB]
embeddings.png [48.8 KB]
chroma.svg [1.2 MB]
sim.png [26.8 KB]
RAG.mp4 [1.9 MB]
rag.png [81.7 KB]
vectordb.png [16.6 KB]
sbert.png [20.8 KB]
table_rag.png [420.4 KB]
sbert-rerank.png [71.8 KB]
GraphRAG.png [752.8 KB]
📁 llama2_page8
📁 table_images
page_1_1.png [16.3 KB]
page_1_0.png [25.1 KB]
page_1.png [156.4 KB]
chinese_utils.py [979.0 B]
.env [80.0 B]
index.ipynb [319.4 KB]
llama2.pdf [276.7 KB]
rank.py [3.1 KB]
llama2_page8.pdf [176.4 KB]
向量数据库和RAG高级进阶.mp4 [634.7 MB]
📁 day27_基于本地大模型的AI试题系统（实现篇）
📁 转换后的训练集与测试集
train.json [162.2 KB]
test.json [51.6 KB]
📁 数据转换代码
test_data.py [1.1 KB]
data_utils.py [2.0 KB]
📁 Lora模型与训练日志
📁 checkpoint-1300
README.md [5.0 KB]
optimizer.pt [282.1 MB]
scheduler.pt [1.0 KB]
rng_state.pth [13.9 KB]
tokenizer.json [10.9 MB]
training_args.bin [5.6 KB]
adapter_model.safetensors [140.9 MB]
adapter_config.json [762.0 B]
trainer_state.json [55.4 KB]
tokenizer_config.json [6.7 KB]
special_tokens_map.json [485.0 B]
training_args.yaml [766.0 B]
nohup.out [262.2 KB]
📁 标注后的数据
高考生物选择题02.csv [35.0 KB]
高考生物选择题01.csv [77.1 KB]
【录播】基于本地大模型的AI试题系统（实现篇）.mp4 [1.6 GB]
📁 day22_llama-index实现RAG
📁 demo_22
📁 data
README_zh-CN.md [12.7 KB]
pdf内容研报.pdf [189.1 KB]
📁 storage
graph_store.json [18.0 B]
image__vector_store.json [72.0 B]
index_store.json [1.9 KB]
docstore.json [74.5 KB]
default__vector_store.json [175.9 KB]
test02.py [1.6 KB]
download_hf.py [177.0 B]
app.py [2.7 KB]
test03.py [956.0 B]
test01.py [534.0 B]
test04.py [2.1 KB]
【课件】Llama_index实现RAG.pdf [489.2 KB]
【录播】llama-index实现RAG.mp4 [1.3 GB]
📁 11_Llama3
📁 day_21LLaMa3打包部署（LLaMA-Factory模型评估与量化）
day_21LLaMa3打包部署（LLaMA-Factory模型评估与量化）说明.zip [1.8 MB]
【课件】LLaMa3打包部署（LLaMA-Factory模型评估与量化）.pdf [497.1 KB]
【资料】LLaMa3打包部署（LLaMA-Factory模型评估与量化）.pdf [997.2 KB]
【录播】LLaMa3打包部署（LLaMA-Factory模型评估与量化）.mp4 [899.0 MB]
📁 day_20LLaMa3打包部署教程 (Lora 微调与模型合并）
demo_20.zip [4.3 KB]
【录播】LLaMa3打包部署教程 (Lora 微调与模型合并).mp4 [1.8 GB]
【课件】LLaMa3打包部署（Lora微调与模型合并部署）.pdf [493.1 KB]
【资料】LLaMa3 打包部署教程 (Lora 微调与模型合并部署).pdf [782.6 KB]
📁 day_19LLaMa3微调_使用 LLaMA-Factory微调Llama3
【资料】LLaMa3微调（使用 LLaMA-Factory 微调 LLaMA3）.pdf [140.9 KB]
【录播】LLaMA_Factory微调Llama3.mp4 [881.6 MB]
【课件】LLaMa3微调（使用 LLaMA-Factory 微调 LLaMA3）.pdf [602.0 KB]
demo_19.zip [4.3 KB]
data.zip [280.1 KB]
📁 day_18Llama3大模型本地部署与调用
【录播】Llama3大模型本地部署与调用.mp4 [877.9 MB]
【资料】Llama3大模型本地部署与调用.pdf [1.2 MB]
【课件】llama3大模型本地部署与调用.pdf [555.2 KB]
【资料】Llama3大模型本地部署与调用(1).pdf [1.5 MB]
📁 day_22LLaMa3打包部署（大模型转换为 GGUF 以及使用 ollama 运行）
📁 Llama-3-8B-Instruct
📁 qlora
📁 train_2024-11-27-21-02-24
📁 checkpoint-150
README.md [5.0 KB]
adapter_config.json [763.0 B]
tokenizer.json [16.4 MB]
rng_state.pth [13.9 KB]
trainer_state.json [6.0 KB]
tokenizer_config.json [49.9 KB]
adapter_model.safetensors [80.1 MB]
training_args.bin [5.3 KB]
special_tokens_map.json [325.0 B]
scheduler.pt [1.0 KB]
optimizer.pt [160.4 MB]
📁 checkpoint-100
tokenizer.json [16.4 MB]
rng_state.pth [13.9 KB]
optimizer.pt [160.4 MB]
special_tokens_map.json [325.0 B]
training_args.bin [5.3 KB]
README.md [5.0 KB]
adapter_model.safetensors [80.1 MB]
adapter_config.json [763.0 B]
trainer_state.json [4.3 KB]
tokenizer_config.json [49.9 KB]
scheduler.pt [1.0 KB]
adapter_config.json [763.0 B]
trainer_state.json [6.2 KB]
README.md [1.6 KB]
training_args.yaml [844.0 B]
llamaboard_config.yaml [1.7 KB]
tokenizer.json [16.4 MB]
all_results.json [359.0 B]
special_tokens_map.json [325.0 B]
training_args.bin [5.3 KB]
adapter_model.safetensors [80.1 MB]
trainer_log.jsonl [5.9 KB]
eval_results.json [174.0 B]
tokenizer_config.json [49.9 KB]
train_results.json [220.0 B]
training_eval_loss.png [23.1 KB]
running_log.txt [15.7 KB]
training_loss.png [43.9 KB]
【录播】LLaMa3打包部署（大模型转换为 GGUF 以及使用 ollama 运行） .mp4 [862.9 MB]
【课件】LLaMa3打包部署（大模型转换为 GGUF 以及使用 ollama 运行）.pdf [568.0 KB]
【录播】LLaMa3打包部署（大模型转换为 GGUF 以及使用 ollama 运行） -笔记.PanD [93.0 B]
【资料】LLaMa3打包部署（大模型转换为 GGUF 以及使用 ollama 运行）.pdf [219.3 KB]
11_Llama3资料.zip [1.8 MB]
📁 03_LangChain基础
📁 day06_LangChain Chat Model
day06_LangChain Chat Model说明.png [493.5 KB]
redis-3.2.100_x64.zip [4.9 MB]
【语雀】LangChain Chat Model.txt [106.0 B]
【录播】LangChain Chat Model.mp4 [793.0 MB]
【MD】LangChain Chat Model.md [57.1 KB]
【课件】LangChain Chat Model.pdf [872.4 KB]
day6-demo.zip [165.1 KB]
RedisDesktopManager-2022.5.zip [29.1 MB]
【资料】LangChain Chat Model.pdf [3.1 MB]
vs_BuildTools.exe [4.2 MB]
📁 day07_LangChain Tools & Agent
【录播】LangChain Tools & Agent.mp4 [1.6 GB]
【MD】LangChain Tools & Agent.md [62.0 KB]
【资料】LangChain Tools & Agent.pdf [2.8 MB]
day7-demo.zip [1.4 MB]
【语雀】LangChain Tools & Agent.txt [110.0 B]
【课件】LangChain Tools & Agent.pdf [869.8 KB]
📁 day05_LangChain 基础
【MD】LangChain 基础.md [68.0 KB]
【课件】LangChain 基础.pdf [815.1 KB]
day5-demo.zip [16.1 KB]
【语雀】LangChain 基础.txt [102.0 B]
【录播】LangChain 基础.mp4 [596.7 MB]
【资料】LangChain 基础.pdf [3.1 MB]
📁 15 项目实战（聚客一和二期)
📁 day_31基于RAG的线上智能客服系统（部署篇）
📁 lora模型
Qwen2.5-3B-Instruct-lora.zip [2.7 GB]
day_31基于RAG的线上智能客服系统（部署篇）必看.zip [1.8 MB]
【资料】OpenCompass文档.md [22.1 KB]
【课件】基于RAG的线上智能客服系统（部署篇）.pdf [495.8 KB]
【录播】基于RAG的线上智能客服系统（部署篇）.mp4 [1.4 GB]
demo_31.zip [30.9 KB]
📁 day_29基于本地大模型的在线心理问诊系统(部署篇)
📁 项目模型
📁 Qwen1.5-1.8B-Chat_cusm
merges.txt [1.6 MB]
tokenizer_config.json [1.3 KB]
added_tokens.json [80.0 B]
generation_config.json [205.0 B]
tokenizer.json [10.9 MB]
special_tokens_map.json [367.0 B]
model.safetensors [3.4 GB]
vocab.json [2.6 MB]
config.json [748.0 B]
trainer_log.jsonl [42.0 KB]
training_loss.png [55.3 KB]
training_eval_loss.png [40.1 KB]
day_29基于本地大模型的在线心理问诊系统(部署篇)必看.png [493.5 KB]
【课件】基于本地大模型的在线心理问诊系统（部署篇）.pdf [496.7 KB]
【录播】基于本地大模型的在线心理问诊系统(部署篇).mp4 [1.7 GB]
【资料】基于本地大模型的在线心理问诊系统（部署篇）.pdf [271.1 KB]
📁 day33_RAG项目实战（使用llamaindex构建自己的知识库）
RAG_项目源码.zip [11.3 KB]
【资料】RAG项目实战（使用llamaindex构建自己的知识库）.pdf [2.5 MB]
【课件】RAG项目实战（使用llamaindex构建自己的知识库）.pdf [492.4 KB]
【录播】RAG项目实战（使用llamaindex构建自己的知识库）.mp4 [2.3 GB]
📁 day34_视觉项目实战（基于yolo的骨龄识别项目_01）
【课件】视觉项目实战（基于yolo的骨龄识别项目_01）.pdf [761.7 KB]
【录播】视觉项目实战（基于yolo的骨龄识别项目_01）.mp4 [925.6 MB]
【资料】YOLOv5目标侦测教程.pdf [8.5 MB]
📁 day35_视觉项目实战（基于yolo的骨龄识别项目_02）
📁 dataset
arthrosis.zip [141.5 MB]
VOCdevkit.zip [827.4 MB]
📁 day31_demo
📁 yolov5-bone
📁 classify
train.py [16.0 KB]
predict.py [11.5 KB]
val.py [7.9 KB]
tutorial.ipynb [101.2 KB]
📁 segment
train.py [33.9 KB]
val.py [23.4 KB]
predict.py [15.4 KB]
tutorial.ipynb [42.4 KB]
📁 .github
📁 workflows
codeql-analysis.yml [2.0 KB]
greetings.yml [5.4 KB]
docker.yml [1.6 KB]
stale.yml [2.3 KB]
links.yml [1.7 KB]
ci-testing.yml [7.5 KB]
translate-readme.yml [708.0 B]
📁 ISSUE_TEMPLATE
config.yml [358.0 B]
feature-request.yml [1.7 KB]
question.yml [1.1 KB]
bug-report.yml [2.9 KB]
dependabot.yml [441.0 B]
PULL_REQUEST_TEMPLATE.md [774.0 B]
📁 runs
📁 train
📁 exp
📁 weights
best.pt [54.2 MB]
last.pt [54.2 MB]
train_batch2.jpg [526.6 KB]
opt.yaml [1.1 KB]
hyp.yaml [401.0 B]
train_batch1.jpg [582.7 KB]
results.csv [25.6 KB]
labels.jpg [133.3 KB]
labels_correlogram.jpg [234.9 KB]
train_batch0.jpg [573.4 KB]
📁 detect
📁 exp5
📁 crops
📁 MCP
15483.jpg [21.5 KB]
147322.jpg [4.1 KB]
1547.jpg [11.6 KB]
15474.jpg [11.6 KB]
147324.jpg [5.1 KB]
15263.jpg [8.1 KB]
15473.jpg [10.0 KB]
147323.jpg [5.0 KB]
1526.jpg [7.0 KB]
15472.jpg [9.9 KB]
15482.jpg [21.9 KB]
1548.jpg [28.4 KB]
15484.jpg [26.5 KB]
14732.jpg [4.4 KB]
15262.jpg [7.2 KB]
15264.jpg [8.8 KB]
📁 Radius
14732.jpg [11.0 KB]
1526.jpg [15.3 KB]
1548.jpg [57.1 KB]
1547.jpg [21.9 KB]
📁 Ulna
14732.jpg [7.8 KB]
1526.jpg [9.9 KB]
1548.jpg [31.3 KB]
1547.jpg [15.3 KB]
📁 ProximalPhalanx
15472.jpg [9.7 KB]
15475.jpg [8.5 KB]
1548.jpg [18.6 KB]
15263.jpg [7.0 KB]
15484.jpg [24.2 KB]
147323.jpg [4.7 KB]
14732.jpg [3.2 KB]
147325.jpg [4.9 KB]
15262.jpg [6.2 KB]
15264.jpg [8.8 KB]
15474.jpg [10.4 KB]
15485.jpg [22.3 KB]
1526.jpg [6.8 KB]
147322.jpg [4.7 KB]
15473.jpg [10.2 KB]
147324.jpg [4.4 KB]
1547.jpg [9.5 KB]
15483.jpg [25.3 KB]
15265.jpg [8.7 KB]
15482.jpg [24.1 KB]
📁 DistalPhalanx
15472.jpg [8.8 KB]
14732.jpg [4.8 KB]
147325.jpg [4.0 KB]
1526.jpg [7.5 KB]
1547.jpg [8.5 KB]
15474.jpg [11.0 KB]
15265.jpg [7.4 KB]
15264.jpg [10.8 KB]
15483.jpg [28.5 KB]
15484.jpg [34.7 KB]
15262.jpg [6.6 KB]
15482.jpg [30.3 KB]
147324.jpg [3.7 KB]
1548.jpg [28.2 KB]
147322.jpg [4.0 KB]
15263.jpg [7.4 KB]
147323.jpg [3.2 KB]
15485.jpg [26.8 KB]
15475.jpg [14.9 KB]
15473.jpg [10.1 KB]
📁 MCPFirst
1547.jpg [16.2 KB]
1526.jpg [13.2 KB]
1548.jpg [39.0 KB]
14732.jpg [7.5 KB]
📁 MiddlePhalanx
15482.jpg [16.2 KB]
1526.jpg [5.1 KB]
15264.jpg [6.8 KB]
15484.jpg [19.6 KB]
15262.jpg [6.8 KB]
15263.jpg [6.0 KB]
15474.jpg [7.8 KB]
1548.jpg [20.5 KB]
1547.jpg [9.1 KB]
147324.jpg [3.5 KB]
147323.jpg [3.0 KB]
147322.jpg [3.9 KB]
14732.jpg [3.7 KB]
15472.jpg [8.5 KB]
15483.jpg [19.6 KB]
15473.jpg [7.4 KB]
1548.png [6.3 MB]
1547.png [3.9 MB]
1526.png [2.9 MB]
14732.png [1.6 MB]
📁 exp4
1526.png [2.9 MB]
1548.png [6.3 MB]
14732.png [1.6 MB]
1547.png [3.9 MB]
📁 exp2
14732.png [1.6 MB]
1548.png [6.3 MB]
1547.png [3.9 MB]
📁 exp3
1548.png [6.3 MB]
14732.png [1.6 MB]
1526.png [2.9 MB]
1547.png [3.9 MB]
📁 exp
1548.png [6.3 MB]
1547.png [3.9 MB]
📁 __pycache__
val.cpython-310.pyc [13.8 KB]
export.cpython-310.pyc [30.5 KB]
hubconf.cpython-310.pyc [5.1 KB]
📁 models
📁 __pycache__
common.cpython-310.pyc [36.1 KB]
experimental.cpython-310.pyc [4.7 KB]
__init__.cpython-310.pyc [136.0 B]
yolo.cpython-310.pyc [15.7 KB]
📁 hub
yolov5-fpn.yaml [1.2 KB]
yolov5n6.yaml [1.8 KB]
yolov5s-ghost.yaml [1.4 KB]
yolov3-spp.yaml [1.5 KB]
yolov5-bifpn.yaml [1.4 KB]
yolov5-p6.yaml [1.7 KB]
yolov5x6.yaml [1.8 KB]
yolov5s-LeakyReLU.yaml [1.5 KB]
yolov5l6.yaml [1.8 KB]
yolov3-tiny.yaml [1.2 KB]
anchors.yaml [3.3 KB]
yolov5s6.yaml [1.8 KB]
yolov5s-transformer.yaml [1.4 KB]
yolov5-panet.yaml [1.4 KB]
yolov3.yaml [1.5 KB]
yolov5-p2.yaml [1.6 KB]
yolov5m6.yaml [1.8 KB]
yolov5-p7.yaml [2.1 KB]
yolov5-p34.yaml [1.3 KB]
📁 segment
yolov5s-seg.yaml [1.4 KB]
yolov5x-seg.yaml [1.4 KB]
yolov5l-seg.yaml [1.4 KB]
yolov5m-seg.yaml [1.4 KB]
yolov5n-seg.yaml [1.4 KB]
common.py [40.8 KB]
yolov5x.yaml [1.4 KB]
yolov5m.yaml [1.4 KB]
yolov5l.yaml [1.4 KB]
tf.py [26.4 KB]
experimental.py [4.2 KB]
yolo.py [17.4 KB]
yolov5n.yaml [1.4 KB]
yolov5s.yaml [1.4 KB]
__init__.py
📁 data
📁 scripts
get_coco.sh [1.5 KB]
download_weights.sh [641.0 B]
get_coco128.sh [619.0 B]
get_imagenet.sh [1.6 KB]
📁 hyps
hyp.scratch-low.yaml [1.7 KB]
hyp.no-augmentation.yaml [1.6 KB]
hyp.scratch-med.yaml [1.6 KB]
hyp.Objects365.yaml [674.0 B]
hyp.scratch-high.yaml [1.6 KB]
hyp.VOC.yaml [1.1 KB]
📁 images
1526.png [1.0 MB]
1548.png [2.3 MB]
14732.png [584.9 KB]
1547.png [1.3 MB]
coco128.yaml [1.8 KB]
coco.yaml [2.4 KB]
coco128-seg.yaml [1.8 KB]
Argoverse.yaml [2.7 KB]
Objects365.yaml [9.0 KB]
ImageNet.yaml [18.4 KB]
SKU-110K.yaml [2.3 KB]
GlobalWheat2020.yaml [1.8 KB]
VOC.yaml [3.4 KB]
VisDrone.yaml [2.9 KB]
xView.yaml [5.0 KB]
mydata.yaml [600.0 B]
📁 utils
📁 flask_rest_api
README.md [1.7 KB]
example_request.py [369.0 B]
restapi.py [1.4 KB]
📁 google_app_engine
Dockerfile [821.0 B]
app.yaml [174.0 B]
additional_requirements.txt [187.0 B]
📁 docker
Dockerfile [2.6 KB]
Dockerfile-cpu [1.7 KB]
Dockerfile-arm64 [1.6 KB]
📁 segment
📁 __pycache__
__init__.cpython-310.pyc [143.0 B]
general.cpython-310.pyc [5.0 KB]
augmentations.py [3.7 KB]
metrics.py [5.3 KB]
plots.py [6.2 KB]
dataloaders.py [13.5 KB]
loss.py [8.4 KB]
general.py [5.7 KB]
__init__.py
📁 __pycache__
bone_filter_utils.cpython-310.pyc [847.0 B]
autoanchor.cpython-310.pyc [6.3 KB]
metrics.cpython-310.pyc [11.0 KB]
callbacks.cpython-310.pyc [2.7 KB]
downloads.cpython-310.pyc [4.2 KB]
augmentations.cpython-310.pyc [13.4 KB]
loss.cpython-310.pyc [6.1 KB]
__init__.cpython-310.pyc [2.7 KB]
autobatch.cpython-310.pyc [2.5 KB]
plots.cpython-310.pyc [21.0 KB]
dataloaders.cpython-310.pyc [42.3 KB]
bone_utils.cpython-310.pyc [837.0 B]
general.cpython-310.pyc [36.8 KB]
torch_utils.cpython-310.pyc [16.4 KB]
📁 loggers
📁 clearml
📁 __pycache__
__init__.cpython-310.pyc [151.0 B]
clearml_utils.cpython-310.pyc [5.8 KB]
README.md [10.6 KB]
clearml_utils.py [7.8 KB]
__init__.py
hpo.py [5.1 KB]
📁 __pycache__
__init__.cpython-310.pyc [13.2 KB]
📁 wandb
📁 __pycache__
wandb_utils.cpython-310.pyc [6.8 KB]
__init__.cpython-310.pyc [149.0 B]
wandb_utils.py [8.1 KB]
__init__.py
📁 comet
📁 __pycache__
__init__.cpython-310.pyc [14.4 KB]
comet_utils.cpython-310.pyc [4.1 KB]
__init__.py [18.3 KB]
README.md [10.5 KB]
hpo.py [6.5 KB]
optimizer_config.json [2.9 KB]
comet_utils.py [4.6 KB]
__init__.py [16.1 KB]
📁 aws
resume.py [1.2 KB]
__init__.py
mime.sh [780.0 B]
userdata.sh [1.2 KB]
torch_utils.py [19.2 KB]
augmentations.py [16.6 KB]
triton.py [3.5 KB]
plots.py [24.1 KB]
__init__.py [2.6 KB]
dataloaders.py [54.5 KB]
callbacks.py [2.6 KB]
metrics.py [14.2 KB]
general.py [44.4 KB]
activations.py [3.4 KB]
loss.py [9.7 KB]
downloads.py [4.8 KB]
autoanchor.py [7.2 KB]
bone_filter_utils.py [622.0 B]
bone_utils.py [675.0 B]
autobatch.py [2.9 KB]
README.zh-CN.md [39.6 KB]
.dockerignore [3.6 KB]
LICENSE [33.7 KB]
test08.py [900.0 B]
export.py [40.2 KB]
CONTRIBUTING.md [4.9 KB]
yolov5s.pt [14.1 MB]
benchmarks.py [7.8 KB]
setup.cfg [1.7 KB]
tutorial.ipynb [40.0 KB]
.gitignore [3.9 KB]
images_tag.py [1.4 KB]
.gitattributes [75.0 B]
test1.py [1.1 KB]
train.py [33.2 KB]
CITATION.cff [393.0 B]
detect.py [14.0 KB]
val.py [20.0 KB]
requirements.txt [1.5 KB]
.pre-commit-config.yaml [1.7 KB]
hubconf.py [7.6 KB]
voc_to_yolo.py [2.6 KB]
README.md [40.5 KB]
📁 hand_bone_detect
📁 templates
client.html [574.0 B]
result.html [238.0 B]
📁 detect_result
detect.jpg [1.4 MB]
📁 params
MCP_best.pth [42.7 MB]
Radius_best.pth [42.7 MB]
PIP_best.pth [42.7 MB]
DIP_best.pth [42.7 MB]
DIPFirst_best.pth [42.7 MB]
MCPFirst_best.pth [42.7 MB]
PIPFirst_best.pth [42.7 MB]
MIP_best.pth [42.7 MB]
Ulna_best.pth [42.7 MB]
📁 cutpictures
MIPFifth.png [25.4 KB]
MCPFifth.png [37.7 KB]
Radius.png [81.5 KB]
PIPFifth.png [28.2 KB]
PIPThird.png [37.1 KB]
PIPFirst.png [38.1 KB]
MCPFirst.png [63.9 KB]
MCPThird.png [43.5 KB]
DIPFifth.png [33.6 KB]
DIPFirst.png [55.3 KB]
DIPThird.png [42.5 KB]
Ulna.png [53.2 KB]
MIPThird.png [32.6 KB]
📁 img
1548.png [2.3 MB]
📁 test_data
example.jpg [689.3 KB]
detect_bone.py [2.9 KB]
common.py [7.0 KB]
test.py [995.0 B]
main.py [1.7 KB]
flask_test_img.py [1.3 KB]
bone_filter_utils.py [622.0 B]
detect_utils.py [3.3 KB]
bone_detect_ui.ui [2.3 KB]
📁 hand_test
📁 logs
📁 MCPFirst_loss_train_avg_loss
events.out.tfevents.1688785342.DESKTOP-BT6NS4S.13268.1 [4.1 KB]
📁 Radius_loss_train_avg_loss
events.out.tfevents.1688796343.DESKTOP-BT6NS4S.13268.9 [3.9 KB]
📁 PIP_loss_train_avg_loss
events.out.tfevents.1688801475.DESKTOP-BT6NS4S.13268.13 [2.4 KB]
📁 MIP_loss_MIP
📁 val_avg_losses
events.out.tfevents.1688792192.DESKTOP-BT6NS4S.13268.8 [3.7 KB]
📁 PIPFirst_loss_train_avg_loss
events.out.tfevents.1688789961.DESKTOP-BT6NS4S.13268.5 [4.1 KB]
📁 DIPFirst_loss_DIPFirst
📁 val_avg_losses
events.out.tfevents.1688787690.DESKTOP-BT6NS4S.13268.4 [4.1 KB]
📁 MCP_loss_train_avg_loss
events.out.tfevents.1688891547.DESKTOP-BT6NS4S.11960.3 [3.1 KB]
📁 DIPFirst_loss_train_avg_loss
events.out.tfevents.1688787690.DESKTOP-BT6NS4S.13268.3 [4.1 KB]
📁 Ulna_loss_Ulna
📁 val_avg_losses
events.out.tfevents.1688799016.DESKTOP-BT6NS4S.13268.12 [3.8 KB]
📁 Ulna_loss_train_avg_loss
events.out.tfevents.1688799016.DESKTOP-BT6NS4S.13268.11 [3.8 KB]
📁 PIPFirst_loss_PIPFirst
📁 val_avg_losses
events.out.tfevents.1688789961.DESKTOP-BT6NS4S.13268.6 [4.1 KB]
📁 DIP_loss_DIP
📁 val_avg_losses
events.out.tfevents.1688888129.DESKTOP-BT6NS4S.11960.2 [3.7 KB]
📁 Radius_loss_Radius
📁 val_avg_losses
events.out.tfevents.1688796343.DESKTOP-BT6NS4S.13268.10 [3.9 KB]
📁 MIP_loss_train_avg_loss
events.out.tfevents.1688792192.DESKTOP-BT6NS4S.13268.7 [3.7 KB]
📁 PIP_loss_PIP
📁 val_avg_losses
events.out.tfevents.1688801475.DESKTOP-BT6NS4S.13268.14 [2.4 KB]
📁 DIP_loss_train_avg_loss
events.out.tfevents.1688888129.DESKTOP-BT6NS4S.11960.1 [3.7 KB]
📁 MCPFirst_loss_MCPFirst
📁 val_avg_losses
events.out.tfevents.1688785342.DESKTOP-BT6NS4S.13268.2 [4.1 KB]
📁 MCP_loss_MCP
📁 val_avg_losses
events.out.tfevents.1688891547.DESKTOP-BT6NS4S.11960.4 [3.1 KB]
events.out.tfevents.1688888077.DESKTOP-BT6NS4S.11960.0 [7.7 KB]
events.out.tfevents.1688785315.DESKTOP-BT6NS4S.13268.0 [29.1 KB]
📁 params
DIP_best.pth [42.7 MB]
PIPFirst_best.pth [42.7 MB]
MCP_best.pth [42.7 MB]
DIPFirst_best.pth [42.7 MB]
MCPFirst_best.pth [42.7 MB]
Ulna_best.pth [42.7 MB]
Radius_best.pth [42.7 MB]
MIP_best.pth [42.7 MB]
PIP_best.pth [42.7 MB]
📁 utils
data_set.py [1.6 KB]
tools.py [805.0 B]
data_utils.py [2.5 KB]
trainer.py [3.7 KB]
test1.py [244.0 B]
【课件】视觉项目实战（基于yolo的骨龄识别项目_02）.pdf [805.9 KB]
【录播】视觉项目实战（基于yolo的骨龄识别项目_02）.mp4 [920.7 MB]
📁 day_30基于RAG的线上智能客服系统（微调篇）
【课件】基于RAG的线上智能客服系统（微调篇）.pdf [494.6 KB]
demo_30.zip [1.7 KB]
项目背景.png [149.3 KB]
data.zip [2.2 MB]
【录播】基于RAG的线上智能客服系统（微调篇）.mp4 [1.2 GB]
📁 day_27基于本地大模型的在线心理问诊系统（训练篇）
【资料】xtuner微调大模型教程.pdf [173.0 KB]
【录播】基于本地大模型的在线心理问诊系统（训练篇01）.mp4 [1.2 GB]
项目流程.png [103.1 KB]
data.zip [17.0 MB]
【课件】基于本地大模型的在线心理问诊系统（训练篇）.pdf [497.8 KB]
demo_27.zip [2.6 KB]
📁 day_28基于本地大模型的在线心理问诊系统（训练篇）
📁 llamafactory数据集转换代码
data_utils.py [2.3 KB]
📁 xtuner环境
requirements.txt [4.3 KB]
📁 xtuner模型训练配置文件
qwen1_5_1_8b_chat_qlora_alpaca_e3.py [7.5 KB]
internlm2_5_chat_7b_qlora_oasst1_e3.py [8.0 KB]
📁 data
xtuner_data.zip [5.8 MB]
llama_factory_data.zip [5.5 MB]
output_conversations.csv [18.1 MB]
【录播】基于本地大模型的在线心理问诊系统（训练篇02）.mp4 [990.3 MB]
📁 day_32基于pytorch的语音识别与语音唤醒
📁 本地存储index的RAG
📁 storage
default__vector_store.json [361.0 KB]
graph_store.json [18.0 B]
image__vector_store.json [72.0 B]
docstore.json [171.4 KB]
index_store.json [3.6 KB]
📁 data
【资料】OpenCompass文档.md [22.1 KB]
data.csv [29.2 KB]
rag.py [2.7 KB]
【课件】扩展项目（基于pytorch实现的语音识别）.pdf [491.6 KB]
【录播】扩展项目（基于pytorch的语音识别与语音唤醒）.mp4 [1.8 GB]
语音应用场景.png [67.8 KB]
📁 12_多模态
📁 day_23多模态（多模态大模型的概念与本地部署调用）
day_23多模态（多模态大模型的概念与本地部署调用）说明.zip [1.8 MB]
文生视频效果.mp4 [360.9 KB]
【资料】多模态（多模态大模型的概念与本地部署调用）.pdf [4.9 MB]
【录播】多模态大模型的概念与本地部署调用.mp4 [1.2 GB]
【课件】多模态（多模态大模型的概念与本地部署调用）.pdf [731.7 KB]
📁 00_Python基础
5-PyCharn安装与应用.mp4 [22.9 MB]
14-爬虫（1）.mp4 [33.2 MB]
7-Python工程应用-字符串.mp4 [32.3 MB]
11-Python程序调式和异常处理技巧.mp4 [95.6 MB]
4-VSCode安装与应用.mp4 [19.4 MB]
12-JSON应用.mp4 [40.1 MB]
6-pip包管理工具.mp4 [28.7 MB]
10-字符编码的处理.mp4 [64.7 MB]
1-初始Python.mp4 [9.6 MB]
13-文件IO.mp4 [25.3 MB]
16-爬虫（3）.mp4 [63.9 MB]
9-如何使用注解.mp4 [29.1 MB]
8-Python文档化应用场景.mp4 [19.0 MB]
15-爬虫（2）.mp4 [76.7 MB]
17-爬虫（4）.mp4 [66.9 MB]
2-Windows环境安装.mp4 [6.6 MB]
3-macOS环境安装.mp4 [6.8 MB]
19.dotenv使用.mp4 [31.3 MB]
20.FastAPI的使用.mp4 [59.6 MB]
18-字符串处理.mp4 [50.7 MB]
📁 10_modelScope
📁 day_17ModeScope在线训练平台&服务器选配训练模型
【资料】ModeScope在线训练平台&服务器选配训练模型.pdf [275.8 KB]
demo_17.zip [27.8 MB]
【课件】ModeScope在线训练平台&服务器选配训练模型.pdf [539.7 KB]
【录播】ModeScope在线训练平台&服务器选配训练模型.mp4 [1.1 GB]
📁 13_llamaindex
📁 day_24Llama_Index（核心组件介绍）
demo_24.zip [4.9 MB]
【课件】Llama_Index（核心组件介绍）.pdf [486.3 KB]
【录播】Llama_Index（核心组件介绍）.mp4 [1.5 GB]
llama_index0.8.3.zip [108.1 MB]
【资料】Llama_Index（核心组件介绍）.pdf [624.0 KB]
📁 day_25llamaindex实战（使用llamaindex构建自己的知识库）
【资料】llamaindex实战（使用llamaindex构建自己的知识库）.pdf [2.2 MB]
【课件】llamaindex实战（使用llamaindex构建自己的知识库）.pdf [491.4 KB]
【录播】llamaindex实战（使用llamaindex构建自己的知识库）.mp4 [1.0 GB]
demo_25.zip [9.0 KB]
📁 05_Rag基础
📁 day09_RAG 专题
【资料】RAG 专题.pdf [2.7 MB]
【录播】RAG 专题.mp4 [788.8 MB]
【课件】RAG 专题.pdf [863.5 KB]
【MD】RAG 专题.md [54.2 KB]
day9-demo.zip [286.2 KB]
【语雀】RAG 专题.txt [96.0 B]
📁 08_LangGraph
📁 day12_LangGraph
【课件】LangGraph.pdf [866.0 KB]
【录播】LangGraph.mp4 [798.7 MB]
day12-demo.zip [127.0 KB]
【资料】LangGraph.pdf [2.5 MB]
【语雀】LangGraph.txt [95.0 B]
【MD】LangGraph.md [129.8 KB]
📁 01_AI及LLM基础
📁 day01_AI领域基础概念
day1-demo.zip [14.3 KB]
【录播】AI 领域基础概念.mp4 [1.1 GB]
OpenAI-HK 操作指南.pdf [151.1 KB]
【课件】AI 领域基础概念.pdf [7.6 MB]
【MD】AI 领域基础概念.md [49.9 KB]
【资料】AI 领域基础概念.pdf [1.7 MB]
【语雀】AI 领域基础概念.txt [110.0 B]
OpenAI.apifox.json [244.5 KB]
📁 day03_支持多模态输入的 AI Chatbot App
【MD】支持多模态输入的 AI Chatbot App.md [3.6 KB]
【录播】支持多模态输入的 AI Chatbot App.mp4 [1.5 GB]
【课件】支持多模态输入的 AI Chatbot App.pdf [839.0 KB]
day3-demo.zip [787.7 KB]
【语雀】支持多模态输入的 AI Chatbot App.txt [125.0 B]
【资料】支持多模态输入的 AI Chatbot App.pdf [2.9 MB]
📁 day02_OpenAI 开发
【课件】OpenAI 开发.pdf [1.6 MB]
【资料】OpenAI 开发.pdf [642.8 KB]
【MD】OpenAI 开发.md [6.9 KB]
【录播】OpenAI 开发.mp4 [601.6 MB]
day2-demo.zip [766.1 KB]
【语雀】OpenAI 开发.txt [99.0 B]
📁 14_AutoGen Studio
📁 day_26AutoGen Studio调用本地大模型实现多Agent应用
【录播】AutoGen Studio调用本地大模型实现多Agent应用.mp4 [834.2 MB]
【课件】AutoGen Studio入门使用.pdf [598.4 KB]
【资料】AutoGen Studio入门使用.pdf [858.8 KB]
📁 09_Hugging Face
📁 day_13Hugging Face 核心组件介绍
【课件】Hugging Face 核心组件介绍.pdf [502.4 KB]
demo_13.zip [1.1 GB]
【资料】Hugging Face 核心组件介绍.pdf [312.9 KB]
【录播】Hugging Face 核心组件介绍.mp4 [1.7 GB]
📁 day_16Hugging Face 模型微调训练（GPT2-中文生成模型定制化微调训练）
【资料】Hugging Face 模型微调训练（GPT2-中文生成模型定制化微调训练）.pdf [323.9 KB]
【课件】Hugging Face 模型微调训练（GPT2-中文生成模型定制化微调训练）.pdf [513.9 KB]
【录播】Hugging Face 模型微调训练（GPT2-中文生成模型定制化微调训练）.mp4 [802.8 MB]
demo_16.zip [27.8 MB]
📁 day_14Hugging Face 模型微调训练（基于 BERT 的中文评价情感分析）
【课件】Hugging Face 模型微调训练（基于 BERT 的中文评价情感分析）.pdf [503.5 KB]
【资料】Hugging Face 模型微调训练（基于 BERT 的中文评价情感分析）.pdf [743.2 KB]
【录播】Hugging Face 模型微调训练（基于 BERT 的中文评价情感分析）.mp4.mp4 [766.4 MB]
📁 day_15Hugging Face 模型微调训练（如何处理超长文本训练问题）
【课件】Hugging Face 模型微调训练（如何处理超长文本训练问题）.pdf [498.9 KB]
【资料】Hugging Face 模型微调训练（如何处理超长文本训练问题）.pdf [361.4 KB]
model.zip [364.5 MB]
【录播】Hugging Face 模型微调训练（如何处理超长文本训练问题）.mp4 [801.4 MB]
📁 04_Embedding基础
📁 day08_Embedding 与向量数据库
【语雀】Embedding 与向量数据库.txt [114.0 B]
【资料】Embedding 与向量数据库.pdf [6.5 MB]
day8-demo.zip [1.2 MB]
【MD】Embedding 与向量数据库.md [96.4 KB]
【录播】Embedding 与向量数据库.mp4 [705.2 MB]
【课件】Embedding 与向量数据库.pdf [867.5 KB]
AI大模型学习路径.pdf [676.5 KB]
大神指南.docx [1.4 MB]
000.夸克手机注册领取1TB方法.png [295.3 KB]