Instructions to use altndrr/cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use altndrr/cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="altndrr/cased", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("altndrr/cased", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add requirements to README.md
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print(f"{labels[index]:>16s}: {100 * value.item():.2f}%")
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```
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## Citation
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```latex
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print(f"{labels[index]:>16s}: {100 * value.item():.2f}%")
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```
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The model depends on some libraries you have to install manually before execution:
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```bash
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pip install torch faiss-cpu flair inflect nltk transformers
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```
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## Citation
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```latex
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