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, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-mpnet") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-mpnet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 07169d78595436906617998fa1a8b65ebc58846e12f51b31e181b50bf727c8e4
- Size of remote file:
- 950 kB
- SHA256:
- 7ec28bc9e5e0b39c01009827592251806c747558f30775fa98f608003e5f18eb
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