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:
- af578d9b15e9068b58cbe1574a327b8af84e17b9bfc0b11890a58da8826141bd
- Size of remote file:
- 12.9 MB
- SHA256:
- 102ed396707c522591f3a3bffa49434bde5b85a44ac8d0528a98bb1ee94f9892
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