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This repository contains demos for the Transformers library by HuggingFace, a popular NLP and computer vision library.
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
A PyTorch-based toolkit for speech processing, including ASR, speaker recognition, and speech enhancement.
A collaboration-friendly studio for building NeRF-based 3D reconstructions using PyTorch and other ML tools.
A comprehensive Python learning resource covering AI, machine learning, web scraping, and more.
A PyTorch implementation of the U-Net for image semantic segmentation with high quality images.
Kornia is a Python library for geometric computer vision and spatial AI tasks.
The AI developer platform to train and fine-tune models, and manage models from experimentation to production.
A PyTorch package for the discrete VAE used in DALLยทE, an AI model for generating images from text prompts.
Large Language Model Text Generation Inference library for developers working with AI tools and models.
YOLOv3 is a popular open-source object detection library for computer vision tasks, with support for multiple deployment targets.
YOLOX is a high-performance anchor-free YOLO model for object detection
An elegant PyTorch deep reinforcement learning library for vibe coders building AI-powered applications.
Pre-trained Chinese BERT model with whole word masking, useful for natural language processing tasks.
A deep learning library for text-to-speech applications, focusing on generating high-quality speech from text.
Fast and accurate machine learning framework that can build models in just 3 lines of Python code.
A collection of techniques for deep learning with satellite and aerial imagery, including object detection and classification.
A distributed system for running large language models (LLMs) on personal devices, enabling faster fine-tuning and inference.
A Python library for secure and private machine learning using federated learning and differential privacy
LeetCUDA is a comprehensive collection of modern CUDA learning resources, including 200+ CUDA kernels, Tensor Cores, HGEMM, and FA-2 MMA.
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