Instructions to use hf-internal-testing/tiny-random-mpnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-mpnet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-mpnet")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-mpnet") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-mpnet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9ed6188cdadf163db5ebf05a1e8d1b442fb3f16bb639ef79c9c1a96be931261
- Size of remote file:
- 1.28 MB
- SHA256:
- 139ddc2641eb1ef117621d0380fabd1fd6aa3cc21bc27a10501c6c2fd720b9d5
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