The official GitHub page for the survey paper "A Survey of Large Language Models".

An open-source framework for training large multimodal models.

Painter & SegGPT Series: Vision Foundation Models from BAAI

PyTorch implementation of VALL-E(Zero-Shot Text-To-Speech), Reproduced Demo https://lifeiteng.github.io/valle/index.html

Emu Series: Generative Multimodal Models from BAAI

🔥🔥 UNO: A Universal Customization Method for Both Single and Multi-Subject Conditioning

OpenICL is an open-source framework to facilitate research, development, and prototyping of in-context learning.

Papers and Datasets on Instruction Tuning and Following. ✨✨✨

[ACL 2024] An Easy-to-use Instruction Processing Framework for LLMs.

A curated list of awesome instruction tuning datasets, models, papers and repositories.

[ICLR 2023] Code for the paper "Binding Language Models in Symbolic Languages"

🧠🔗 Graph-Based Programmable Neuro-Symbolic LM Framework - a production-first LM framework built with decade old Deep Learning best practices

VisualCloze: A universal image generation framework that can support a wide range of in-domain tasks and generalize to unseen ones. (🔥 🔥 🔥 Merged into offical pipelines of diffusers.)

🎁[ChatGPT4NLU] A Comparative Study on ChatGPT and Fine-tuned BERT

[NeurIPS2023] Official implementation and model release of the paper "What Makes Good Examples for Visual In-Context Learning?"

Official implementation of the paper "Linear Transformers with Learnable Kernel Functions are Better In-Context Models"

Grimoire is All You Need for Enhancing Large Language Models

[ICLR 2023] Code for our paper "Selective Annotation Makes Language Models Better Few-Shot Learners"

Experiments and code to generate the GINC small-scale in-context learning dataset from "An Explanation for In-context Learning as Implicit Bayesian Inference"

[ICML 2023] Code for our paper “Compositional Exemplars for In-context Learning”.