Instructions to use hf-internal-testing/tiny-random-T5Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-T5Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-T5Model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-T5Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-T5Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b9ec5b28bf3e88319ddefbba116e8411913a88427d53ba9498c5e0373646658
- Size of remote file:
- 4.61 MB
- SHA256:
- 6d64278e2391b6346e84ad7528b5ffbc65f4c5206c54370de3cbd38bf9ef5019
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