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 tokenizer_config.json from microsoft/mpnet-base: direct link, hf CLI and curl.
- Browser
- Download file 48 Bytes
-
https://huggingface.co/microsoft/mpnet-base/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://microsoft/mpnet-base/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/microsoft/mpnet-base/resolve/main/tokenizer_config.json
48 Bytes
| {"model_max_length": 512, "do_lower_case": true} |