A latent text-to-image diffusion model

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Learn how to design, develop, deploy and iterate on production-grade ML applications.

Google Research

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

Instruct-tune LLaMA on consumer hardware

A guidance language for controlling large language models.

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

A collection of various deep learning architectures, models, and tips

StableLM: Stability AI Language Models

Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

This repository contains implementations and illustrative code to accompany DeepMind publications

PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)

Scripts for fine-tuning Meta Llama3 with composable FSDP & PEFT methods to cover single/multi-node GPUs. Supports default & custom datasets for applications such as summarization and Q&A. Supportin…

Public facing notes page

YSDA course in Natural Language Processing

LAVIS - A One-stop Library for Language-Vision Intelligence

My blogs and code for machine learning. http:https://cnblogs.com/pinard

Build your neural network easy and fast, 莫烦Python中文教学

tensorflow2中文教程，持续更新(当前版本:tensorflow2.0)，tag: tensorflow 2.0 tutorials

Using Low-rank adaptation to quickly fine-tune diffusion models.

Create Magic Story!

links to conference publications in graph-based deep learning

The image prompt adapter is designed to enable a pretrained text-to-image diffusion model to generate images with image prompt.

PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners

Acceptance rates for the major AI conferences

VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.