Instructions to use ydshieh/tiny-random-LiltForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-LiltForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ydshieh/tiny-random-LiltForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-LiltForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("ydshieh/tiny-random-LiltForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8cb44a2a06abe4598baaa7b310c92ab3869537cd9c35f82df7ab56b431d1470
- Size of remote file:
- 278 kB
- SHA256:
- c4b456f29263e377f2b93e5411e788d86a3e2821227c5e2ea54b3dd6b6aa112e
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