Instructions to use hf-tiny-model-private/tiny-random-LiltForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-LiltForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-LiltForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-LiltForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-LiltForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bb73f377a68a8a5b0fd60feb05180402b3fd3979dfc2ba6b3f43a63a659c035c
- Size of remote file:
- 278 kB
- SHA256:
- 3f983dc617839aa589476e1a665140008b7b3d12a9c8df24349b01b4a81493c0
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