🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
- nlp
- natural-language-processing
- pytorch
- pytorch-transformers
Repository Index
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A high-throughput and memory-efficient inference and serving engine for LLMs
Complete API layer for private AI applications on local models: RAG, skills, tools, MCP, text-to-sql, and more. Works with any OpenAI-compatible inference server.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
A generative speech model for daily dialogue.
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 Llama) RAG and Agent app with langchain
- chatglm
- langchain
- llm
- knowledge-base
SGLang is a high-performance serving framework for large language models and multimodal models.
Faster Whisper transcription with CTranslate2
- deep-learning
- inference
- quantization
- speech-recognition
DeepInfer: High-performance, large-scale inference framework for DeepSeek models
Multi-lingual large voice generation model, providing inference, training and deployment full-stack ability.
- audio-generation
- gpt-4o
- text-to-speech
- tts
LLM inference server with continuous batching & SSD caching for Apple Silicon — managed from the macOS menu bar
Open-source speech recognition toolkit for training, inference, streaming ASR, VAD, punctuation, speaker diarization pipelines, and OpenAI-compatible/MCP serving.
- pytorch
- speech-recognition
- paraformer
- punctuation
Machine Learning Engineering Open Book
A Flexible Framework for Experiencing Heterogeneous LLM Inference/Fine-tune Optimizations
Nano vLLM
TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.
20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.
- llm
- llmops
- model-inference
- fine-tuning
LMCache: Supercharge Your LLM with the Fastest KV Cache Layer
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
- bloom
- deep-learning
- distributed-systems
- language-models
《深入理解 AI Infra：量化分析与系统设计》（李博杰 著）开源书稿：从硬件约束和模型架构出发，量化推导 LLM 推理与训练系统设计。含全书正文、PDF、配套计算工具与实验
- accelerator
- ai-infra
- ai-infrastructure
- book
Superduper: End-to-end framework for building custom AI applications and agents.
- ai
- mlops
- torch
- transformers
Serve large Qwen models fast on the GPUs you actually own. Qwen3.8-27B on a single 24 GB card with vLLM: 127 tok/s single-user (381 when the answer quotes the prompt), ~1,035 tok/s at 64 concurrent, 150k-262k context. vLLM patches, requant pipeline, benchmarks.
- kv-cache
- llm-inference
- local-llm
- quantization
Open decision models from 0.8B to 27B: a calibrated probability for every option in one pass, and a short thought only when unsure. Engine for vLLM, llama.cpp and MLX.
- agents
- calibration
- classification
- decision-making