Instructions to use hf-internal-testing/tiny-random-onnx-mt5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-onnx-mt5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-onnx-mt5")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-onnx-mt5") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-onnx-mt5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a6bad68c6f61b3c59c6af3ff3bb805190229380e4fe63af656cbdb1ba7a80486
- Size of remote file:
- 18.1 MB
- SHA256:
- 728f60112bd2377b5ff8a823d8f8b1d0b18283ca8aae6b171590e81c1707b213
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