Instructions to use mukund/privbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mukund/privbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mukund/privbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mukund/privbert") model = AutoModelForMaskedLM.from_pretrained("mukund/privbert", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download .gitattributes from mukund/privbert: direct link, hf CLI and curl.
- Browser
- Download file 690 Bytes
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https://huggingface.co/mukund/privbert/resolve/main/.gitattributes
- Command line
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hf download hf://mukund/privbert/.gitattributes
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curl -L -o .gitattributes https://huggingface.co/mukund/privbert/resolve/main/.gitattributes
690 Bytes
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