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:
- d37590c485b3c77649b1d5f6ed4cdd3477dfa7de78fe07d29d44baa8d553c8a6
- Size of remote file:
- 1.08 MB
- SHA256:
- 02dc62d1263db9c2f876e75ce19c5dd21be614bbd8bc1d36c78820ef23da2419
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