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:
- fa4642f7b62ce01ff6b3719ebeb8795815478720173364507cb41adefe214ff7
- Size of remote file:
- 278 kB
- SHA256:
- 6ae89c0563e339a625bd00d36f029e1385f925f680f404f0d99a7d1938723984
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