Multi-label image classification datasets compatible with timm (>= v1.0.31)
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Computer Vision
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timm
PyTorch Image Models (timm) is a collection of image models, layers, utilities, optimizers, schedulers, data-loaders / augmentations, and reference training / validation scripts that aim to pull together a wide variety of SOTA models with ability to reproduce ImageNet training results.
- Find all the timm models here.
- timm github repository
- timm documentation 📚
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timm/deepseek_vit_412m.deepseek_v4_1_flash
Image Feature Extraction • 0.4B • Updated • 301 • 2 -
timm/deepseek_vit_412m.deepseek_v4_flash_vision_exp
Image Feature Extraction • 0.4B • Updated • 33 -
timm/deepseek_vit_412m_align.deepseek_v4_1_flash
Image Feature Extraction • 0.5B • Updated • 53 -
timm/deepseek_vit_412m_enc.deepseek_v4_1_flash
Image Feature Extraction • 0.5B • Updated • 105
Multi-label image classification datasets compatible with timm (>= v1.0.31)
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timm/deepseek_vit_412m.deepseek_v4_1_flash
Image Feature Extraction • 0.4B • Updated • 301 • 2 -
timm/deepseek_vit_412m.deepseek_v4_flash_vision_exp
Image Feature Extraction • 0.4B • Updated • 33 -
timm/deepseek_vit_412m_align.deepseek_v4_1_flash
Image Feature Extraction • 0.5B • Updated • 53 -
timm/deepseek_vit_412m_enc.deepseek_v4_1_flash
Image Feature Extraction • 0.5B • Updated • 105
spaces 6
Running
Agents
87
The timm Leaderboard
🏆
Compare and visualize PyTorch image model performance metrics
Running
Agents
4
timm CAM
📚
Explain image content using AI models
Running
Agents
7
Timm + Transformers
😻
Any timm model with the transformers integration
Paused
3
JupyterLab (timm)
💻
Improved JuptyerLab template w/ timm
Running
Agents
18
timm Attention Visualization
👁
Visualize attention maps for images using timm models
models 1,813
timm/qwen3_vit_306m_merge.qwen_drive_1_0_4b
Image Feature Extraction • 0.3B • Updated • 52
timm/qwen3_vit_306m_enc.qwen_drive_1_0_4b
Image Feature Extraction • 0.3B • Updated • 70
timm/qwen3_vit_306m.qwen_drive_1_0_4b
Image Feature Extraction • 0.3B • Updated • 149
timm/deepseek_vit_412m_enc.deepseek_v4_flash_vision_exp
Image Feature Extraction • 0.5B • Updated • 37 • 1
timm/deepseek_vit_412m_enc.deepseek_v4_1_flash
Image Feature Extraction • 0.5B • Updated • 105
timm/deepseek_vit_412m_align.deepseek_v4_flash_vision_exp
Image Feature Extraction • 0.5B • Updated • 42
timm/deepseek_vit_412m_align.deepseek_v4_1_flash
Image Feature Extraction • 0.5B • Updated • 53
timm/deepseek_vit_412m.deepseek_v4_flash_vision_exp
Image Feature Extraction • 0.4B • Updated • 33
timm/deepseek_vit_412m.deepseek_v4_1_flash
Image Feature Extraction • 0.4B • Updated • 301 • 2
timm/efficientvim_m4_dist.in1k
Image Classification • 21.2M • Updated • 28
datasets 21
timm/imet-open-access
Viewer • Updated • 260k • 89
timm/bigearthnet-v2-rgb
Viewer • Updated • 480k • 193
timm/bigearthnet-v2-rgb-nir-swir
Viewer • Updated • 480k • 90
timm/nih-chest-xray-14
Viewer • Updated • 112k • 779
timm/plant-pathology-2021
Viewer • Updated • 18.6k • 1.34k • 12
timm/amazon-from-space
Viewer • Updated • 203k • 64
timm/bee-dataset
Viewer • Updated • 7.49k • 40
timm/mini-imagenet
Viewer • Updated • 65k • 6.17k • 28
timm/imagenet-22k-wds
Viewer • Updated • 123k • 6.83k • 14
timm/imagenet-12k-wds
Viewer • Updated • 127k • 3.71k • 10