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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("microsoft/mpnet-base") model = AutoModelForMaskedLM.from_pretrained("microsoft/mpnet-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from microsoft/mpnet-base: direct link, hf CLI and curl.
- Browser
- Download file 536 MB
-
https://huggingface.co/microsoft/mpnet-base/resolve/main/tf_model.h5
- Command line
-
hf download hf://microsoft/mpnet-base/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/microsoft/mpnet-base/resolve/main/tf_model.h5
536 MB
- Xet hash:
- 7fc890b66f6f248776059320ed75843987bfb691a34818c62c90f60ee2e9ec97
- Size of remote file:
- 536 MB
- SHA256:
- 3c249c072b75151b3d66fd7a6cc494f840b78e3a7a7e7bf78c1634ef9a9b759d
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