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:
- f41d2f5d9959a04ffa8e3a26da9f4334dd15b58583ea6590e07343e53703136b
- Size of remote file:
- 1.06 MB
- SHA256:
- 4084a3474b80dda6046dfdcdd592dfd3c96c10685456f12fc1fdb59a2078bd17
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