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:
- 48284f6bf0587603b9b1d9f867196e024883332a1159a24d4d68934db756be00
- Size of remote file:
- 4.47 MB
- SHA256:
- 596b95ab1ee5ab4e7189e0913237b4ef627e63bb5203aed033e8ca65f34c90b3
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