Lists (3)
Stars
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.
Google Research
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
StableLM: Stability AI Language Models
Companion webpage to the book "Mathematics For Machine Learning"
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
This repository contains implementations and illustrative code to accompany DeepMind publications
Official inference library for Mistral models
[NeurIPS 2024 Best Paper Award][GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction". A…
An annotated implementation of the Transformer paper.
Taming Transformers for High-Resolution Image Synthesis
A course in reinforcement learning in the wild
Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.
PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
Reference models and tools for Cloud TPUs.
Go to https://github.com/pytorch/tutorials - this repo is deprecated and no longer maintained
TensorFlow Basic Tutorial Labs
PyTorch implementation of AnimeGANv2
VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.
Official codebase used to develop Vision Transformer, SigLIP, MLP-Mixer, LiT and more.
Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)
We unified the interfaces of instruction-tuning data (e.g., CoT data), multiple LLMs and parameter-efficient methods (e.g., lora, p-tuning) together for easy use. We welcome open-source enthusiasts…
A data generation pipeline for creating semi-realistic synthetic multi-object videos with rich annotations such as instance segmentation masks, depth maps, and optical flow.
Beyond Accuracy: Behavioral Testing of NLP models with CheckList