Instructions to use hf-internal-testing/tiny-random-MPNetModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MPNetModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-MPNetModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MPNetModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MPNetModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5768e4632557a684da6bb380eee9a146e6b640ffe1917d9d056d6b7ec8f323c
- Size of remote file:
- 954 kB
- SHA256:
- 99bd3796d43ab6f07a9fc30da5d9b8f560e8476e4ec0e715fcd8dd8362779208
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