Instructions to use AyaF/ASL-Vit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AyaF/ASL-Vit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="AyaF/ASL-Vit") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("AyaF/ASL-Vit") model = AutoModelForImageClassification.from_pretrained("AyaF/ASL-Vit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from AyaF/ASL-Vit: direct link, hf CLI and curl.
- Browser
- Download file 560 Bytes
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https://huggingface.co/AyaF/ASL-Vit/resolve/refs%2Fpr%2F2/README.md
- Command line
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hf download hf://AyaF/ASL-Vit@refs/pr/2/README.md
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curl -L -o README.md https://huggingface.co/AyaF/ASL-Vit/resolve/refs%2Fpr%2F2/README.md
560 Bytes
| tags: | |
| - image-classification | |
| - pytorch | |
| - huggingpics | |
| metrics: | |
| - accuracy | |
| - Precision | |
| - Recall | |
| - F1Score | |
| model-index: | |
| - name: ArSL VIT | |
| results: | |
| - task: | |
| name: Image Classification | |
| type: image-classification | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.9934656620025635 | |
| - name: Precision | |
| type: Precision | |
| value: 0.9939382672309875 | |
| - name: Recall | |
| type: Recall | |
| value: 0.9934656620025635 | |
| - name: F1Score | |
| type: F1Score | |
| value: 0.9933341145515442 | |