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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68e20d1987cb2447a140107791ae210b3a3d3e2eddca43c377ab37ebd7e8f5f0
- Size of remote file:
- 1.01 MB
- SHA256:
- 53d54060a8d81d1df97be5c45f7b628a1142d5683ab02f9dbeb48eec2d4bed44
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