Instructions to use hf-tiny-model-private/tiny-random-T5Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-T5Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-T5Model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-T5Model") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-T5Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9ceea815a8b63a874fed41b0780b362d63cfd88af959aab1b9e7990696eada6
- Size of remote file:
- 4.49 MB
- SHA256:
- 9cfe33f52a24ac30aa8763d554f386b210154ad12a2fe875c883d3d12f11d935
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