Instructions to use hf-internal-testing/tiny-random-ElectraForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ElectraForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-ElectraForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ElectraForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-ElectraForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5cb97dda926e484a71d553ca062de52337e65ab02f23d03c51bb5d68396a68a8
- Size of remote file:
- 1.13 MB
- SHA256:
- 9166a201eb465dc10327281aa7ea6fcdd4dcd74cb6adc4126b7f8d73cdf12f31
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