instruction-tuning

Research Trends in LLM-guided Multimodal Learning.

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

“百聆”是一个基于LLaMA的语言对齐增强的英语/中文大语言模型，具有优越的英语/中文能力，在多语言和通用任务等多项测试中取得ChatGPT 90%的性能。BayLing is an English/Chinese LLM equipped with advanced language alignment, showing superior capability in English/Chinese generation, instruction following and multi-turn interaction.⚠️ This project has been moved to: https://github.com/BayLing-Models/BayLing

Code/Data for the paper: "LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding"

(AAAI 2024) BLIVA: A Simple Multimodal LLM for Better Handling of Text-rich Visual Questions

The official codes for "Aurora: Activating chinese chat capability for Mixtral-8x7B sparse Mixture-of-Experts through Instruction-Tuning"

Code for instruction-tuning Stable Diffusion.

Awesome LLM Papers and repos on very comprehensive topics.

Datasets collection and preprocessings framework for NLP extreme multitask learning

Resources on Large Language Models for Table Processing

An LLM training framework built from the ground up, featuring a custom BumbleBee architecture and end-to-end support for multiple open-source models across Pretraining → SFT → RLHF/DPO.

🚀 Easy, open-source LLM finetuning with one-line commands, seamless cloud integration, and popular optimization frameworks. ✨

[NAACL 2024] MMC: Advancing Multimodal Chart Understanding with LLM Instruction Tuning

🚀 LLaMA-MoE v2: Exploring Sparsity of LLaMA from Perspective of Mixture-of-Experts with Post-Training

Awesome Multimodal Assistant is a curated list of multimodal chatbots/conversational assistants that utilize various modes of interaction, such as text, speech, images, and videos, to provide a seamless and versatile user experience.

This repo contains a list of channels and sources from where LLMs should be learned

🤖 language modeling sft demos

[NeurIPS 2023 Main Track] This is the repository for the paper titled "Don’t Stop Pretraining? Make Prompt-based Fine-tuning Powerful Learner"

An benchmark for evaluating the capabilities of large vision-language models (LVLMs)

Multimodal Instruction Tuning for Llama 3