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:
- 6cd8fb1b746b9c23f67fd8916ac8ae3d9a80daba8142086a6e4735b35e8b0a11
- Size of remote file:
- 1.03 MB
- SHA256:
- c91c95fc805f9c0a3d4c7e39c4b97d3016db237f03374628080578dbcc14b41e
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