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, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-UMT5Model") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-UMT5Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed74dae216a765ba199ea41bc7aa9c4be7f8415412463114a3ae73d455355135
- Size of remote file:
- 33.2 MB
- SHA256:
- fd8a761d290c94d87704f8cc77967dd5c43268959a253596702762339b1a06a8
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