# PyTorch Implementation

This is an unconditional diffusion model for generating cute butterfly images, built based on the content of Unit 1 of the Hugging Face Diffusion Model Course.

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

This is a fine-tuning example model based on the second unit of the diffusion model course, designed for unconditional image generation tasks.

This is an unconditional diffusion model for generating adorable butterfly images, developed based on the first unit of Hugging Face's diffusion model course.

UPerNet semantic segmentation model based on Swin Transformer architecture, suitable for high-precision image segmentation tasks

UPerNet semantic segmentation model based on Swin Transformer small architecture, suitable for scene parsing tasks like ADE20K

UPerNet is a semantic segmentation model based on the ConvNeXt-Tiny architecture, suitable for image segmentation tasks.

UPerNet semantic segmentation model based on ConvNeXt-Large encoder, suitable for scene parsing tasks like ADE20K

UPerNet is a semantic segmentation model based on the ConvNeXt-Small architecture, suitable for image segmentation tasks.

UPerNet image segmentation model based on ConvNeXt-Tiny encoder, suitable for semantic segmentation tasks

PyTorch-based DeepLabV3Plus image segmentation model supporting efficient semantic segmentation tasks

A PyTorch-based FPN architecture image segmentation model supporting multiple encoders, suitable for semantic segmentation tasks.

A PyTorch-based image segmentation model library supporting various encoder-decoder architectures for semantic segmentation tasks

A Transformer-based semantic segmentation model optimized for the ADE20K dataset

This is an unconditional diffusion model for generating adorable butterfly images, implemented using PyTorch and the Diffusers library.

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

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

This is an unconditional diffusion model for generating cute butterfly images, implemented with PyTorch and Diffusers library.

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

A satellite image segmentation model based on the UNet architecture with integrated spatial attention mechanism, specifically designed for cloud detection tasks in multispectral data.

This is an unconditional diffusion model for generating adorable butterfly images, implemented based on PyTorch and Diffusers library.

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

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

This is an unconditional image generation model based on the Diffusion Model, specifically fine-tuned for butterfly images.

A PyTorch-based image segmentation model using Transformer architecture for dense prediction tasks

fast3r is a model focused on image-to-3D conversion, developed by Facebook Research.

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

UPerNet is an image segmentation model implemented in PyTorch, supporting semantic segmentation tasks.

PAN is an image segmentation model implemented in PyTorch, utilizing pyramid attention mechanisms to enhance feature extraction capabilities

DeepLabV3 is a semantic segmentation model implemented in PyTorch, suitable for image segmentation tasks.

PSPNet is a deep learning model for semantic segmentation that uses pyramid pooling modules to capture multi-scale contextual information

A PyTorch-based semantic segmentation model utilizing multi-scale attention mechanisms, suitable for image segmentation tasks

A semantic segmentation model based on PyTorch, utilizing an improved UNet++ architecture, suitable for image segmentation tasks.

Unet image segmentation model implemented in PyTorch, supporting multiple encoder architectures

A semantic segmentation model based on the Segformer architecture, optimized for the Cityscapes dataset

A lightweight semantic segmentation model based on Segformer architecture, pre-trained on the Cityscapes dataset

A semantic segmentation model based on the Segformer architecture, specifically optimized for the Cityscapes dataset

Semantic segmentation model based on Segformer architecture, optimized for Cityscapes dataset

A lightweight semantic segmentation model based on the Segformer architecture, pretrained on the ADE20K dataset

PyTorch-based Segformer model for semantic segmentation tasks, pre-trained on the ADE20K dataset