Instructions to use microsoft/mpnet-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/mpnet-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="microsoft/mpnet-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("microsoft/mpnet-base") model = AutoModelForMaskedLM.from_pretrained("microsoft/mpnet-base") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e20e7a467207e33cd8909510b1db79f707f47822ab714ee5d2f9620153c74838
- Size of remote file:
- 532 MB
- SHA256:
- f8eb85dab52341af018fb8cd325a9d83fdb00871c1b2cb1d445d42b289c1d45e
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