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:
- 87c5e58f94f1e0ebd184b197bc3420e2006b0e95536171328e2977f721cbc9be
- Size of remote file:
- 33.2 MB
- SHA256:
- 3710042f19415b7ea6c96eb0b45d3df2b07c4f294823c845e9e2814a194da6d5
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