MoBA: Mixture of Block Attention for Long-Context LLMs

Flash-Linear-Attention models beyond language

A collection of resources and papers on Diffusion Models

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Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset

[NeurIPS 2024] Official Repository of The Mamba in the Llama: Distilling and Accelerating Hybrid Models

该仓库主要记录 大模型（LLMs） 算法工程师相关的面试题

Code for paper [Neat: Nonlinear Parameter-efficient Adaptation of Pre-trained Models]

Awesome Knowledge Distillation

🚀 Efficient implementations of state-of-the-art linear attention models in Torch and Triton

✨✨Latest Advances on Multimodal Large Language Models

Code for paper [Low-Rank Interconnected Adaptation across Layers]

An efficient, flexible and full-featured toolkit for fine-tuning LLM (InternLM2, Llama3, Phi3, Qwen, Mistral, ...)

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

Lecture materials for Cornell CS5785 Applied Machine Learning (Fall 2024)

Speech To Speech: an effort for an open-sourced and modular GPT4-o

[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

Collection of AWESOME vision-language models for vision tasks

LLM inference in C/C++

Stanford NLP Python library for Representation Finetuning (ReFT)

A simple and efficient Mamba implementation in pure PyTorch and MLX.

A Survey on multimodal learning research.

Solve puzzles. Learn CUDA.

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

Building blocks for foundation models.

Fast and memory-efficient exact attention

Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models"

[ICML2024 (Oral)] Official PyTorch implementation of DoRA: Weight-Decomposed Low-Rank Adaptation