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:
- 549ae90bdcc87bdcb8574598deba5a29c5401b664076f27938dd24465ed06190
- Size of remote file:
- 33.2 MB
- SHA256:
- d8ae201eb19d6f79dc38dce7c75046d3d28277ac1f6bec84e4ab244c8a625577
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