Instructions to use hf-internal-testing/tiny-random-XmodForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XmodForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-XmodForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-XmodForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-XmodForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e979542b866c06fc4f39a500de818bb7da2d1093d87624894db87719b6c7a8ac
- Size of remote file:
- 32.2 MB
- SHA256:
- bc77dad34e9318ec3ece577673dfcd7132ea81afca943c6e97d79b19678bdc14
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