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🤗 Evaluate: A library for easily evaluating machine learning models and datasets.
DSIR large-scale data selection framework for language model training
Finetune Llama 3.1, Mistral, Phi & Gemma LLMs 2-5x faster with 80% less memory
Minimalistic large language model 3D-parallelism training
Manage scalable open LLM inference endpoints in Slurm clusters
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.
Freeing data processing from scripting madness by providing a set of platform-agnostic customizable pipeline processing blocks.
NSCC is a high-performance computing center in Singapore.
Easy-to-use LLM fine-tuning framework (LLaMA-2, BLOOM, Falcon, Baichuan, Qwen, ChatGLM2)
Implementation of rectified flow and some of its followup research / improvements in Pytorch
An efficient, flexible and full-featured toolkit for fine-tuning LLM (InternLM2, Llama3, Phi3, Qwen, Mistral, ...)
Let's build better datasets, together!
Papers from the computer science community to read and discuss.
A collection of inspiring lists, manuals, cheatsheets, blogs, hacks, one-liners, cli/web tools and more.
A WebUI for Efficient Fine-Tuning of 100+ LLMs (ACL 2024)
Integrate cutting-edge LLM technology quickly and easily into your apps
This is the Mixture-of-Agents (MoA) concept, adapted from the original work by TogetherAI. My version is tailored for local model usage and features a user-friendly Gradio interface.
Together Mixture-Of-Agents (MoA) – 65.1% on AlpacaEval with OSS models
Pioneering in Vietnamese Multimodal Large Language Model
C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
An elegant PyTorch deep reinforcement learning library.
Efficient implementations of Needleman-Wunsch and other sequence alignment algorithms written in Rust with Python bindings via PyO3.
Mispronunciation Detection using a pretrained and finetuned wav2vec2 model for phoneme recognition and diagnosis and feedback using large language model
MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities (ICML 2024)
Measuring Massive Multitask Language Understanding | ICLR 2021
