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:
- 97221aac5f1710f41b08eed4082e7de3b20aff6383e7d059cfa239654394724d
- Size of remote file:
- 4.47 MB
- SHA256:
- 1f0f956cfd25b728551c463ed5a5a942ea3c87fda9c757a61e8d172eda949053
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