Image Classification
Transformers
Safetensors
ortho_vit
computer-vision
vit
vision-transformer
linear-residual-updates
imagenet
custom_code
Instructions to use BootsofLagrangian/linear-vit-b-imagenet1k-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BootsofLagrangian/linear-vit-b-imagenet1k-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="BootsofLagrangian/linear-vit-b-imagenet1k-hf", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("BootsofLagrangian/linear-vit-b-imagenet1k-hf", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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| Steps | Connection | Top-1 Accuracy (%) | Top-5 Accuracy (%) | Link |
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| 90k | Orthogonal | **74.62** | 92.26 | [link](https://huggingface.co/BootsofLagrangian/ortho-vit-b-imagenet1k-hf) |
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| 90k | Linear | 71.23 | 90.29 | [here](https://huggingface.co/BootsofLagrangian/linear-vit-b-imagenet1k-hf) |
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| Steps | Connection | Top-1 Accuracy (%) | Top-5 Accuracy (%) | Link |
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| 90k | Orthogonal | **74.62** | **92.26** | [link](https://huggingface.co/BootsofLagrangian/ortho-vit-b-imagenet1k-hf) |
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| 90k | Linear | 71.23 | 90.29 | [here](https://huggingface.co/BootsofLagrangian/linear-vit-b-imagenet1k-hf) |
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