Instructions to use hf-tiny-model-private/tiny-random-DistilBertForTokenClassification 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-DistilBertForTokenClassification 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-DistilBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-DistilBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-DistilBertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 42d3553795fd8308ebc2971d8226728e61cfa5dd3c6eb30ce8bd69c8d4ca6ea2
- Size of remote file:
- 355 kB
- SHA256:
- 9e886c0e8e5a865795702d081ba81e8f8500c1ba93b98069878c694ef9718e7d
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