🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
- nlp
- natural-language-processing
- pytorch
- pytorch-transformers
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🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Robust Speech Recognition via Large-Scale Weak Supervision
Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
We write your reusable computer vision tools. 💜
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
OpenMMLab Detection Toolbox and Benchmark
Open-sourced codes for MiniGPT-4 and MiniGPT-v2 (https://minigpt-4.github.io, https://minigpt-v2.github.io/)
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Image-to-Image Translation in PyTorch
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
Original reference implementation of "3D Gaussian Splatting for Real-Time Radiance Field Rendering"
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
Datasets, Transforms and Models specific to Computer Vision
Janus-Series: Unified Multimodal Understanding and Generation Models
CVAT is a leading data annotation platform for image, video, audio, and 3D datasets. It offers open-source, cloud, and enterprise products, as well as labeling services, with AI-assisted labeling, quality assurance, team collaboration, analytics, and developer APIs.
pix2tex: Using a ViT to convert images of equations into LaTeX code.
Image annotation with Python. Supports polygon, rectangle, circle, line, point, and AI-assisted annotation.
Face recognition using Tensorflow
An open source implementation of CLIP.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
A MNIST-like fashion product database. Benchmark :point_down:
🐍 Geometric Computer Vision Library for Spatial AI
A collaboration friendly studio for NeRFs