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:
- dac141efe0a64e9e5b363b2ba9579d006ae60cf7cb061950cd48562c782e6c8d
- Size of remote file:
- 437 kB
- SHA256:
- 398f75b8fd025c2f09cc45a7abdb5e348aaa2f88a02013a6df44b4f326caca7c
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