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, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MPNetModel") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-MPNetModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4aaf9cac0343419017dd550933f668c76bae9e5c8245cd959d04fa5fc0a478e5
- Size of remote file:
- 973 kB
- SHA256:
- 39cff1b6ba9982dc6c4b052eb394330f5a59102a0cbfb9c2ec353e1c7fdb4f39
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