Instructions to use hf-internal-testing/tiny-random-Data2VecTextForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Data2VecTextForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-Data2VecTextForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-Data2VecTextForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-Data2VecTextForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa136e640cb6534ec2cc93a39d2b162c63cb747886f04088e6c0c4c55beaef44
- Size of remote file:
- 368 kB
- SHA256:
- bac9db25857e2a73666624c2eafb37c2a18923441fa4ed61acdd59299fbb552b
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