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:
- 2e45606f862cb38776df6cff9ee3920343a0e066eb743d65ee10c3b9c47b2d5d
- Size of remote file:
- 37.3 MB
- SHA256:
- 0e214819fba97b9556f13b066c499ad8144f098354924cfe9180b5595683ad55
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