Instructions to use hf-internal-testing/tiny-random-T5ForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-T5ForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-T5ForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-T5ForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-T5ForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94cb1b58263deb26db07865359d5ed114b3f0f37d42838d4a2f69bc8ac88c333
- Size of remote file:
- 222 kB
- SHA256:
- b106958e9d8e762d3f22db2016f9022aad6d7b644f1e8cb72419d0b848614b16
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