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DeepRetrieval - Hacking 🔥Real Search Engines and Retrievers with LLM via RL
Real time interactive streaming digital human
Train a 1B LLM with 1T tokens from scratch by personal
ASR + diarization model server with speculative decoding
目前已囊括213个大模型，覆盖chatgpt、gpt-4o、o3-mini、谷歌gemini、Claude3.5、智谱GLM-Zero、文心一言、qwen-max、百川、讯飞星火、商汤senseChat、minimax等商用模型， 以及DeepSeek-R1、qwq-32b、deepseek-v3、qwen2.5、llama3.3、phi-4、glm4、gemma3、mistral、书生in…
GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.
一个go语言的轻量级的快速实现任务调度的框架，支持并发控制、超时控制和重试。框架预置函数执行器和docker执行器，快捷进行函数调度和 docker 调度。
[ACL 2024] Official resources of "ChatKBQA: A Generate-then-Retrieve Framework for Knowledge Base Question Answering with Fine-tuned Large Language Models".
⛷️ LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-training (EMNLP 2024)
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
A repo for update and debug Mixtral-7x8B、MOE、ChatGLM3、LLaMa2、 BaChuan、Qwen an other LLM models include new models mixtral, mixtral 8x7b, training, evaluate and application!
💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
Repo for adapting Meta LlaMA2 in Chinese! META最新发布的LlaMA2的汉化版！ （完全开源可商用）
Official release of InternLM series (InternLM, InternLM2, InternLM2.5, InternLM3).
（1）弹性区间标准化的旋转位置词嵌入编码器+peft LORA量化训练，提高万级tokens性能支持。（2）证据理论解释学习，提升模型的复杂逻辑推理能力（3）兼容alpaca数据格式。
Langchain-Chatchat（原Langchain-ChatGLM）基于 Langchain 与 ChatGLM, Qwen 与 Llama 等语言模型的 RAG 与 Agent 应用 | Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM, Qwen and…
中文nlp解决方案(大模型、数据、模型、训练、推理)
基于ChatGLM-6B、ChatGLM2-6B、ChatGLM3-6B模型，进行下游具体任务微调，涉及Freeze、Lora、P-tuning、全参微调等
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型
🦜🔗 Build context-aware reasoning applications