Instructions to use hf-tiny-model-private/tiny-random-XmodForTokenClassification 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-XmodForTokenClassification 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-XmodForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-XmodForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-XmodForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0484c78b0e0b78ebd21bd686648f175d357596d1dd7bf9284636b228114ceafd
- Size of remote file:
- 32.3 MB
- SHA256:
- 340549c71338ea5e19a8e8cd2e91deb4a53150f1546b7a07a6adfc155886ee58
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