Instructions to use hf-internal-testing/tiny-random-LiltForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LiltForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-LiltForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LiltForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-LiltForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 182d7f932edad16018d7efcd93916433d2f8f8348800d66d3bb2b8b668b5a957
- Size of remote file:
- 294 kB
- SHA256:
- 24ab2fd0356442b48baf89c81c9915086ce7fd411a91dfc444170b7ee2b5f53f
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