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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b26e497a3a5d3e0bad6e0ef8bd019c17d5f8a5e4aa28acd684210b474aaf03b5
- Size of remote file:
- 33.2 MB
- SHA256:
- ff69152de7b25a40b8ff2d8c27ed85cefd5d74b7833f1b309702ca97b8dc5982
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