BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment.

Open standard for machine learning interoperability

📚LeetCUDA: Modern CUDA Learn Notes with PyTorch for Beginners🐑, 200+ CUDA Kernels, Tensor Cores, HGEMM, FA-2 MMA.🎉

博客配套视频链接: https://space.bilibili.com/383551518?spm_id_from=333.1007.0.0 b 站直接看 配套 github 链接：https://github.com/nickchen121/Pre-training-language-model 配套博客链接：https://www.cnblogs.com/nickchen121/p/1…

This repository contains code to train a self-supervised learning model on chest X-ray images that lack explicit annotations and evaluate this model's performance on pathology-classification tasks.

BiomedCLIP data pipeline

RS5M: a large-scale vision language dataset for remote sensing [TGRS]

Official repo for "SkyScript: A Large and Semantically Diverse Vision-Language Dataset for Remote Sensing"

[CVPR 2023] Official repository of paper titled "Fine-tuned CLIP models are efficient video learners".

🛰️ Official repository of paper "RemoteCLIP: A Vision Language Foundation Model for Remote Sensing" (IEEE TGRS)

All notes and materials for the CS229: Machine Learning course by Stanford University

Base codebase for machine learning trainings using camera trap benchmark dataset

Understanding Deep Learning - Simon J.D. Prince

A PyTorch implementation of "MetaFormer: A Unified Meta Framework for Fine-Grained Recognition". A reference PyTorch implementation of “CoAtNet: Marrying Convolution and Attention for All Data Sizes”

[CVPR'25 (Highlight)] Lessons and Insights from a Unifying Study of Parameter-Efficient Fine-Tuning (PEFT) in Visual Recognition

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

Scene and animal attribute retrieval from camera trap data with domain-adapted vision-language models

[EMNLP 2024] Implementation of vision-language model fine-tuning via simple parameter-efficient modification

[ACM TOMM 2023] - Composed Image Retrieval using Contrastive Learning and Task-oriented CLIP-based Features

[CVPR 2022 - Demo Track] - Effective conditioned and composed image retrieval combining CLIP-based features

Code for Finetune like you pretrain: Improved finetuning of zero-shot vision models

Prompt Learning for Vision-Language Models (IJCV'22, CVPR'22)

A PyTorch toolbox for domain generalization, domain adaptation and semi-supervised learning.

An open source implementation of CLIP.

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