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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 430a826878f0b53a6867c7df2e069b539ae424d97f96acf64721e02148359127
- Size of remote file:
- 293 kB
- SHA256:
- f80aeee0d242691cb34563fc162ff9481bab8e7eb7fdc4e8aefe91a43e63cb80
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