An automatic evaluator for instruction-following language models. Human-validated, high-quality, cheap, and fast.

A framework for few-shot evaluation of language models.

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

Optimization Modeling Using mip Solvers and large language models

Train transformer language models with reinforcement learning.

An Easy-to-use, Scalable and High-performance RLHF Framework (70B+ PPO Full Tuning & Iterative DPO & LoRA & Mixtral)

Robust recipes to align language models with human and AI preferences

Code and data for "MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning" (ICLR 2024)

Reformatted Alignment

TrustLLM: Trustworthiness in Large Language Models

Benchmarking large language models' complex reasoning ability with chain-of-thought prompting

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

The MATH Dataset (NeurIPS 2021)

Code and data for "Lost in the Middle: How Language Models Use Long Contexts"

An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.

The official implementation of “Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training”

A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, llama.cpp (GGUF), Llama models.

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

A more memory-efficient rewrite of the HF transformers implementation of Llama for use with quantized weights.

Code for "Learning to summarize from human feedback"

Implementation of paper "Towards a Unified View of Parameter-Efficient Transfer Learning" (ICLR 2022)

Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"