# PyTorch implementation

UPerNet semantic segmentation model based on ConvNeXt-XLarge encoder, suitable for high-precision image segmentation tasks

PyTorch-based Unet image segmentation model supporting various encoder architectures and pre-trained weights

A PyTorch-based semantic segmentation model that supports various encoder architectures, suitable for image segmentation tasks.

A diffusion model based on PyTorch and Diffusers library for unconditional generation of black and white handwritten digit images.

This is a diffusion model fine-tuned on butterfly images using a celebrity face dataset, specifically designed for teaching diffusion model courses.

This is an unconditional image generation model based on diffusion models, specifically designed to generate adorable butterfly images.

This is an unconditional image generation diffusion model based on PyTorch and Diffusers library, specifically designed to generate adorable butterfly images.

A PyTorch-based image classification model for recognizing 12 different room scenes.

Lightweight UNet2D model trained on MNIST dataset for unconditional generation of handwritten digit images

This is an unconditional image generation model based on PyTorch and Diffusers library, specifically designed to generate cute butterfly images.

This is an image classification model built with PyTorch and HuggingPics, primarily used for NSFW (Not Safe For Work) content filtering.

This is an unconditional image generation model based on the diffusion model, specifically designed to generate cute butterfly images.

An image classification model generated by HuggingPics, used to distinguish between deepfake images and real images

This is an image classification model generated by HuggingPics, achieving an accuracy rate of 94.12%.

Object detection model based on YOLOv5m architecture, specifically designed for detecting objects in NFL games

An image classification model built with PyTorch and HuggingPics for recognizing gender in images

Image classification model generated by HuggingPics with an accuracy of 91.67%

This is a Russian sentence embedding model based on PyTorch and Transformers, supporting multi-task processing and capable of generating high-quality sentence vector representations.

This is a large Russian language model based on the BERT architecture, specifically designed for generating sentence embeddings with case-insensitive processing support.

A PyTorch-based facial emotion recognition model trained on the FER2013 dataset with an accuracy of 91.9%.