Instructions to use hf-internal-testing/tiny-random-LongformerForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LongformerForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-LongformerForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LongformerForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-LongformerForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 001112fc5ddb220b0bd847f1b0ba7e155af3fffca0925289d2adb6e803998125
- Size of remote file:
- 412 kB
- SHA256:
- 7409c91392324c8ad8a02e4240b4ae8ca48454c0caccfa7028e64052722f3b55
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