Stars
A complete computer science study plan to become a software engineer.
🤗 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
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
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
A PyTorch native platform for training generative AI models
LLM training code for Databricks foundation models
Structured state space sequence models
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Minimalistic 4D-parallelism distributed training framework for education purpose
Python package for Korean natural language processing.
LLM (Large Language Model) FineTuning
Implementation of paper Data Engineering for Scaling Language Models to 128K Context
🐟 Code and models for the NeurIPS 2023 paper "Generating Images with Multimodal Language Models".
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
Text Adventure Learning Environment Suite - Benchmark to evaluate language models on interactive text environments.
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)