🤗 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.

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

Mamba SSM architecture

An open source implementation of CLIP.

Open Source Neural Machine Translation and (Large) Language Models in PyTorch

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

Modeling, training, eval, and inference code for OLMo

Supercharge Your Model Training

A PyTorch native platform for training generative AI models

LLM training code for Databricks foundation models

Minimalistic 4D-parallelism distributed training framework for education purpose

Python package for Korean natural language processing.

PyTorch-native post-training at scale

Implementation of paper Data Engineering for Scaling Language Models to 128K Context

Minimal implementation of Decision Transformer: Reinforcement Learning via Sequence Modeling in PyTorch for mujoco control tasks in OpenAI gym

Some preliminary explorations of Mamba's context scaling.

🔥 [CVPR2024] Official implementation of "Self-correcting LLM-controlled Diffusion Models (SLD)

A Practitioner's Guide to M(eow)ti Turn Agentic ReinfOrcement learning

Official Code for the WWW'24 Paper: "Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models"

🙈 Code for Zero-shot Triplet Extraction by Template Infilling (Kim et al; IJCNLP-AACL 2023)

https://sites.google.com/view/wngt19/dgt-task