ptrnn

ptrnn's Stars

• meta-llama/llama

  Inference code for Llama models

  Language:Python53.8k5099249.3k

• facebookresearch/segment-anything

  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.

  Language:Jupyter Notebook44.9k2996465.3k

• LAION-AI/Open-Assistant

  OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.

  Language:Python36.8k4231.6k3.2k

• huggingface/peft

  🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

  Language:Python14.6k1099251.4k

• IDEA-Research/Grounded-Segment-Anything

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

  Language:Jupyter Notebook13.9k1143681.3k

• albumentations-team/albumentations

  Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

  Language:Python13.6k1299361.6k

• facebookresearch/ImageBind

  ImageBind One Embedding Space to Bind Them All

  Language:Python8k10083723

• xialeiliu/Awesome-Incremental-Learning

  Awesome Incremental Learning

  3.5k13145551

• OpenGVLab/InternGPT

  InternGPT (iGPT) is an open source demo platform where you can easily showcase your AI models. Now it supports DragGAN, ChatGPT, ImageBind, multimodal chat like GPT-4, SAM, interactive image editing, etc. Try it at igpt.opengvlab.com (支持DragGAN、ChatGPT、ImageBind、SAM的在线Demo系统)

  Language:Python3.1k4349229

• VainF/Awesome-Anything

  General AI methods for Anything: AnyObject, AnyGeneration, AnyModel, AnyTask, AnyX

  1.7k52192

• ytongbai/LVM

  1.6k1291849

• S-LoRA/S-LoRA

  S-LoRA: Serving Thousands of Concurrent LoRA Adapters

  Language:Python1.6k243776

• Ma-Lab-Berkeley/CRATE

  Code for CRATE (Coding RAte reduction TransformEr).

  Language:Python1.1k201782

• facebookresearch/hiera

  Hiera: A fast, powerful, and simple hierarchical vision transformer.

  Language:Python708182836

• caoyunkang/Segment-Any-Anomaly

  Official implementation of "Segment Any Anomaly without Training via Hybrid Prompt Regularization (SAA+)".

  Language:Jupyter Notebook66772870

• awaisrauf/Awesome-CV-Foundational-Models

  42520623

• CroitoruAlin/Diffusion-Models-in-Vision-A-Survey

  This repository categorizes the papers about diffusion models applied in computer vision according to their target task. The classifcation is based on our survey: https://arxiv.org/abs/2209.04747v1

  36014226

• konstmish/prodigy

  The Prodigy optimizer and its variants for training neural networks.

  Language:Python27061615

• GitGyun/visual_token_matching

  [ICLR'23 Oral] Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matching

  Language:Python24871713

• IDEA-Research/UniPose

  Official implementation of the paper "UniPose : Detecting Any Keypoints"

  Language:Python248181610

• lzzcd001/GShell

  Official implentation of "Ghost on the Shell: An Expressive Representation of General 3D Shapes" (ICLR 2024 Oral)

  Language:Python2141788

• garvita-tiwari/PoseNDF

  Implementation of Pose-NDF: Modeling Human Pose Manifolds with Neural Distance Fields

  Language:Python208123319

• impiga/Plain-DETR

  [ICCV2023] DETR Doesn’t Need Multi-Scale or Locality Design

  Language:Python18615235

• zhenxingjian/Partial_Distance_Correlation

  This is the official GitHub for paper: On the Versatile Uses of Partial Distance Correlation in Deep Learning, in ECCV 2022

  Language:Jupyter Notebook1704516

• aliasgharkhani/SLiMe

  1-shot image segmentation using Stable Diffusion

  Language:Python10931110

• aim-uofa/SegPrompt

  Official Implementation of ICCV 2023 Paper - SegPrompt: Boosting Open-World Segmentation via Category-level Prompt Learning

  Language:Python1081011

• locuslab/torchdeq

  Modern Fixed Point Systems using Pytorch

  Language:Python64666

• taldatech/deep-latent-particles-pytorch

  [ICML 2022] Official PyTorch implementation of the paper "Unsupervised Image Representation Learning with Deep Latent Particles"

  Language:Jupyter Notebook25433

• LeslieTrue/CPP

  This is the official implementation for Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models.

  Language:Python23152

• lyumengyao/blad

  Official Implementation of "Box-Level Active Detection (CVPR2023 highlight)"

  Language:Python17440