Instructions to use hf-internal-testing/tiny-random-UMT5Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-UMT5Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-UMT5Model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-UMT5Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-UMT5Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 069da9ce3fba37f001bdc604424f03b2d8dd92cb494f069b4bf95ac136e2af4e
- Size of remote file:
- 33.2 MB
- SHA256:
- 3435a0c293d2ac0fb255c8bb387caf86d31dcc34facdd89ded980e3655004331
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