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:
- 532fedb3ee3c38917553519452dc11e1ba4463e0db209d758f1654af0ecca5f2
- Size of remote file:
- 33.2 MB
- SHA256:
- 5990b2bb329800d584fcc1be7a7c8657d027dff12a9031f74d26c51ab3e50f10
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