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自然语言处理领域下的相关论文（附阅读笔记），复现模型以及数据处理等（代码含TensorFlow和PyTorch两版本）
A collection of LLM papers, blogs, and projects, with a focus on OpenAI o1 🍓 and reasoning techniques.
LLaMA-Omni is a low-latency and high-quality end-to-end speech interaction model built upon Llama-3.1-8B-Instruct, aiming to achieve speech capabilities at the GPT-4o level.
AI Native Data App Development framework with AWEL(Agentic Workflow Expression Language) and Agents
Create book from markdown files. Like Gitbook but implemented in Rust
BookStack，基于MinDoc，使用Beego开发的在线文档管理系统，功能类似Gitbook和看云。
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
text and image to video generation: CogVideoX (2024) and CogVideo (ICLR 2023)
Deployment a light and full OpenAI API for production with vLLM to support /v1/embeddings with all embeddings models.
Code for 'LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders'
A minimal codebase for finetuning large multimodal models, supporting llava-1.5/1.6, llava-interleave, llava-next-video, llava-onevision, llama-3.2-vision, qwen-vl, qwen2-vl, phi3-v etc.
Deploy OpenAI-like Embedding API with LitServe on Studios
✨✨Latest Advances on Multimodal Large Language Models
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
A modular graph-based Retrieval-Augmented Generation (RAG) system
[NeurIPS 2024] SimPO: Simple Preference Optimization with a Reference-Free Reward
This is the first Chinese chat model specifically fine-tuned for Chinese through ORPO based on the Meta-Llama-3-8B-Instruct model.
YaRN: Efficient Context Window Extension of Large Language Models
[ICLR 2024] Efficient Streaming Language Models with Attention Sinks
Easy, fast, and cheap pretrain,finetune, serving for everyone
Rigourous evaluation of LLM-synthesized code - NeurIPS 2023 & COLM 2024
We introduced a new model designed for the Code generation task. Its test accuracy on the HumanEval base dataset surpasses that of GPT-4 Turbo (April 2024) and GPT-4o.