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:
- a6844559670bbae33b7e83593c2a8a172089cdfde78106735a2a1b9e036f8e15
- Size of remote file:
- 32.2 MB
- SHA256:
- 063e9e91b141ff17b289da30810df54ed76943bc7be89106c099ca56fbc2b50c
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