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:
- 9aded2a1b3ed23440b7b6f84b3c02802ea5d272ea4a662c2e06ea3b90675e681
- Size of remote file:
- 222 kB
- SHA256:
- 6e77e65a61e6062701d451cf894982ae34be1f0710ebb29dfb40baa207009536
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