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:
- d75129bbc6b4f13cac2e739b182ea0b111ad37d64a531f2bfcc093213d91544d
- Size of remote file:
- 33.2 MB
- SHA256:
- 7ae90d98dc85f6d1f11d9b53c0c76cbc8283ac05d584c03a977639abb62b4f6d
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