Instructions to use hf-tiny-model-private/tiny-random-MegaForTokenClassification 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-MegaForTokenClassification 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-MegaForTokenClassification")# Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-MegaForTokenClassification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aeadf1758ac8cbb254a7f3bd077bc72764cfeefc6a8a9b5cd83a98d60b96fc8b
- Size of remote file:
- 406 kB
- SHA256:
- 351744d5fcb5f2cefffe7dc12868f7a8c4d3268df44cced30c9116b575036214
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