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An automatic evaluator for instruction-following language models. Human-validated, high-quality, cheap, and fast.
RewardBench: the first evaluation tool for reward models.
Dataset Crafting w/ RAG/Wikipedia ground truth and Efficient Fine-Tuning Using MLX and Unsloth. Includes configurable dataset annotation editor Gradio UI.
Convert Compute And Books Into Instruct-Tuning Datasets (or classifiers)!
Finetune Llama 3.1, Mistral, Phi & Gemma LLMs 2-5x faster with 80% less memory
Large Language Model Text Generation Inference
Scalable Meta-Evaluation of LLMs as Evaluators
An open-sourced LLM judge for evaluating LLM-generated answers.
Arena-Hard-Auto: An automatic LLM benchmark.
AI for all: Build the large graph of the language models
Minimalistic large language model 3D-parallelism training
Easily embed, cluster and semantically label text datasets
A programming framework for agentic AI 🤖
Python SDK, Proxy Server to call 100+ LLM APIs using the OpenAI format - [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, Replicate, Groq]
Superfast AI decision making and intelligent processing of multi-modal data.
All available datasets for Instruction Tuning of Large Language Models
LightEval is a lightweight LLM evaluation suite that Hugging Face has been using internally with the recently released LLM data processing library datatrove and LLM training library nanotron.
A library for easily merging multiple LLM experts, and efficiently train the merged LLM.
Freeing data processing from scripting madness by providing a set of platform-agnostic customizable pipeline processing blocks.
LLM training code for Databricks foundation models
Efficiently Fine-Tune 100+ LLMs in WebUI (ACL 2024)