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:
- a4876ebc5f5e612baf60f6df709e85d909aa65e0d91154311b15923639253ec5
- Size of remote file:
- 558 kB
- SHA256:
- ce07710b7242dc16c1aa689ddb540c2a0587742f2aa63f7e315799cb00d34cf5
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