Instructions to use EMBO/sd-panelization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EMBO/sd-panelization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="EMBO/sd-panelization")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("EMBO/sd-panelization") model = AutoModelForTokenClassification.from_pretrained("EMBO/sd-panelization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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reverting to dataset sd-nlp
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so many typos
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tokenizer files
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licence
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Merge branch 'main' of https://huggingface.co/EMBO/sd-panels into main
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new model
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upload flax model
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allow flax
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model files
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model files
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lfs tracking
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initial commit
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