Instructions to use SharedBailii/PT-POL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SharedBailii/PT-POL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SharedBailii/PT-POL")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SharedBailii/PT-POL") model = AutoModelForMaskedLM.from_pretrained("SharedBailii/PT-POL") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0c38096170e65679d9e9560a05e381a3bb5e9cd3165480fd44c55399dedb6c6
- Size of remote file:
- 1.35 GB
- SHA256:
- f05f7a0cd8264ce58976e362f56936d0304c0faeb9e3afca5ebcca7a74883bfb
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