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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a143c1c8e961d10e59c4b885e4a59f0c48df3e1808b15d1dc028f8ae6e720cde
- Size of remote file:
- 349 kB
- SHA256:
- 3a1135782429a98d6652ced91170a98aeb847e3100e727dab5ee958df933c021
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