{"data":{"slug":"lonepatient-awesome-pretrained-chinese-nlp-models","name":"awesome-pretrained-chinese-nlp-models","tagline":"Curated list of high-quality Chinese pretrained NLP models","github_url":"https://github.com/lonePatient/awesome-pretrained-chinese-nlp-models","owner":"lonePatient","repo":"awesome-pretrained-chinese-nlp-models","owner_avatar_url":"https://avatars.githubusercontent.com/u/35169745?v=4","primary_language":"Python","stars":5579,"forks":514,"topics":["bert","chinese","dataset","ernie","gpt","gpt-2","large-language-models","llm","multimodel","nezha","nlp","nlu-nlg","pangu","pretrained-models","roberta","simbert","xlnet"],"archived":false,"github_pushed_at":"2026-08-14T03:30:33+00:00","maintenance_label":"Very active","stars_delta_30d":8,"url":"https://www.graphcanon.com/tools/lonepatient-awesome-pretrained-chinese-nlp-models","markdown_url":"https://www.graphcanon.com/tools/lonepatient-awesome-pretrained-chinese-nlp-models.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/lonepatient-awesome-pretrained-chinese-nlp-models","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=lonepatient-awesome-pretrained-chinese-nlp-models","description":"Awesome Pretrained Chinese NLP Models，高质量中文预训练模型&大模型&多模态模型&大语言模型集合","homepage_url":null,"license":"MIT","open_issues":6,"watchers":93,"ai_summary":"A collection of high-quality pre-trained Chinese NLP models including large language models and multimodal models.","readme_excerpt":"# Awesome Pretrained Chinese NLP Models\n\n\n\n<div align=\"center\"> \n    <a href=\"https://arxiv.org/pdf/2303.18223.pdf\">论文: A Survey of Large Language Models</a>\n</div>\n\n在自然语言处理领域中，预训练语言模型（Pretrained Language Models）已成为非常重要的基础技术，本仓库主要收集目前网上公开的一些高质量中文预训练模型、中文多模态模型、中文大语言模型等内容(感谢分享资源的大佬)，并将持续更新......\n\n> 国内下载HuggingFace仓库模型推荐使用HuggingFace镜像地址: <https://hf-mirror.com/>\n\n## 📑 目录导航\n\n***\n\n## 📚 模型分类索引\n\n### 🤖 大模型系列\n\n| 分类       | 说明             | 链接                        |\n| :------- | :------------- | :------------------------ |\n| 通用基础大模型  | 参数 >7B 的基础语言模型 | [查看](#Base-LLM)           |\n| 垂直基础大模型  | 金融、医疗、法律等垂直领域  | [查看](#Domain-Base-LLM)    |\n| 通用对话大模型  | 对话式通用语言模型      | [查看](#chatllm)            |\n| 垂直对话大模型  | 垂直领域对话模型       | [查看](#domain-chatllm)     |\n| 多模态对话大模型 | 图文等多模态模型       | [查看](#multimodal-chatllm) |\n| 推理类大模型   | 数学、逻辑推理模型      | [查看](#reasoningllm)       |\n\n### 🔧 预训练模型系列\n\n| 系列            | 代表模型                                                | 链接                        |\n| :------------ | :-------------------------------------------------- | :------------------------ |\n| **NLU系列**     | BERT · RoBERTa · ALBERT · ERNIE · MacBERT · ELECTRA | [查看全部 29 个](docs/nlu-models.md)       |\n| **NLG系列**     | GPT · GPT-3 · T5 · BART · CPM · RWKV                | [查看全部 18 个](docs/nlg-models.md)       |\n| **NLU-NLG系列** | UniLM · GLM · CPT · SimBERT                         | [查看全部 9 个](docs/nlu-nlg-models.md)    |\n| **多模态系列**     | WenLan · CogView · Chinese-CLIP · OFA               | [查看全部 13 个](docs/multimodal-models.md) |\n\n### 📦 资源与工具\n\n[📊 大模型评估基准](#大模型评估基准) · [📦 开源模型库平台](#开源模型库平台) · [📚 开源数据集库](#开源数据集库) · [📝 中文指令数据集](docs/chinese-instruct-datasets.md) · [🎯 Embedding](#Embedding) · [🔗 Other-Awesome](docs/other-awesome.md)\n\n***\n\n**📌 备注说明**\n\n> **ND:** Non-Causal Decoder (非因果解码器) | **CD:** Causal Decoder (因果解码器) | **ED:** Encoder-Decoder (编码器-解码器)\n\n***\n## Base-LLM\n\n> 大规模基础模型：表格中只罗列出参数量`大于7B`以上模型。[查看完整列表 →](docs/base-llm.md)\n\n| 模型                    | 大小                        | 时间      | 语言 | 架构  | 下载                                                                                                                          | 项目                                                                                     | 机构                                                | 备注                                                                                                               |\n| :--- | :--- | :--- | :--- | :--- | :--- | :--- | :--- | :--- |\n| XVERSE-MoE            | 255B / A36B               | 2024-09 | 中英 | MoE | [🤗HF](https://huggingface.co/xverse/XVERSE-MoE-A36B)                                                                       | [GitHub](https://github.com/xverse-ai/XVERSE-MoE-A36B)                                 | xverse-ai                                         | -                                                                                                                |\n| Qwen-2.5              | 0.5\\~72B (7档)             | 2024-09 | 中英 | CD  | [🤗HF](https://huggingface.co/collections/Qwen/qwen25-66e81a666513e518adb90d9e)                                             | [GitHub](https://github.com/QwenLM/Qwen2.5)                                            | QwenLM                                            | [Blog](https://qwenlm.github.io/blog/qwen2.5/)                                                                   |\n| Tele-FLM              | 52B / 102B / 1TB          | 2024-07 | 多语 | CD  | [🤗HF](https://huggingface.co/CofeAI)                                                                                       | -                                                                                      | CofeAI                                            | [Paper](https://arxiv.org/pdf/2404.16645)                                                                        |\n| meta-llama-3.1        | 8B / 70B / 405B           | 2024-07 | 多语 | CD  | [🤗HF](https://huggingface.co/meta-llama)","github_created_at":"2019-05-25T15:46:00+00:00","created_at":"2026-07-07T17:34:54.913387+00:00","updated_at":"2026-08-17T12:01:17.862738+00:00","categories":[{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"bert","name":"bert"},{"slug":"chinese","name":"chinese"},{"slug":"dataset","name":"dataset"},{"slug":"ernie","name":"ernie"},{"slug":"gpt","name":"gpt"},{"slug":"large-language-models","name":"large language models"},{"slug":"multimodel","name":"multimodel"},{"slug":"nlp","name":"nlp"}],"trust":{"provenance":{"is_fork":false,"github_id":188584527,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-17T12:01:17.062Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":0,"days_since_push":3,"last_release_at":null,"stars_delta_30d":8,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:04:21.083Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-17T12:01:17.544Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-08-17T12:01:17.544Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-08-17T12:01:17.544Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When developing applications requiring high-quality, Chinese-specific large language model support","For projects that benefit from a curated selection of both textual and multimodal pretrained models"],"when_not_to_use":["If the application requires extensive Western-language model integration","Projects needing non-Chinese-specific fine-tuning or training will find limited utility"],"source":"enrich:decision_facts","observed_at":"2026-07-14T18:51:19.425Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"A comprehensive collection of advanced Chinese NLP models including large language models and multimodal setups."}]}}