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:
- 3a9525fb192d62d310e705b3033aa0446b01cab1f909f411bff4c1f5645ba219
- Size of remote file:
- 4.46 MB
- SHA256:
- 49ea5d43d99edae73b1b1c4713155825acc12e2386fa44738c7b363c33af2bcd
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