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:
- edbd6bcb9c5d959535ec9439a8f48c6c782937ee663f96abddbf2e6ce3da9a2d
- Size of remote file:
- 12.9 MB
- SHA256:
- 7feb1b8193638e7342ab704b1aef92246935417f3152d3860984d7984a07217e
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