LLM inference in C/C++

AutoAWQ implements the AWQ algorithm for 4-bit quantization with a 2x speedup during inference.

🐚 OpenDevin: Code Less, Make More

SOTA Weight-only Quantization Algorithm for LLMs

Enhanced fork of SWE-bench, tailored for OpenDevin's ecosystem.

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Examples in the MLX framework

SGLang is a structured generation language designed for large language models (LLMs). It makes your interaction with models faster and more controllable.

Easy-to-use LLM fine-tuning framework (LLaMA, BLOOM, Mistral, Baichuan, Qwen, ChatGLM)

A high-throughput and memory-efficient inference and serving engine for LLMs

An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.

Go ahead and axolotl questions

Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.

Toolkit for Elevater Benchmark

Official repository of OFA. Paper: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

UniLM AI - Large-scale Self-supervised Pre-training across Tasks, Languages, and Modalities

Towards Knowledge-Based Personalized Product Description Generation in E-commerce

Code for the article "Semantic-Unit-Based Dilated Convolution for Multi-Label Text Classification" (EMNLP 2018)

Google AI 2018 BERT pytorch implementation

Code of a novel model for NMT

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Python for Linguists – a Gentle Introduction to Programming