Instructions to use hf-internal-testing/tiny-random-BertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-BertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-BertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f44bab3f452e1f5c860424aebe4b5e90d5404bf8fe5313786ef07d3f66e4e0c
- Size of remote file:
- 459 kB
- SHA256:
- 59a5883310dd3027e21bc3b13aecb71cad53301de0d6b5f408ac2b523400305e
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