Instructions to use hf-tiny-model-private/tiny-random-YosoForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-YosoForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-YosoForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-YosoForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-YosoForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cfba3270120aa0295c0392040a92276d918b484ae84bb93dba7f150d55a2210b
- Size of remote file:
- 349 kB
- SHA256:
- 7d28663c5077fd9b24102bedd83030757b3eff941f99be0b44db130b4979c136
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