Instructions to use pucpr-br/cardiobertpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pucpr-br/cardiobertpt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="pucpr-br/cardiobertpt")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("pucpr-br/cardiobertpt") model = AutoModelForMaskedLM.from_pretrained("pucpr-br/cardiobertpt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 617588b29303dbe375d5f2a3c8433e1818177f1e029b40eeacdc024e466c314d
- Size of remote file:
- 712 MB
- SHA256:
- 4e43816adc0fbf9b672567420da1cf7c3e1b4cfb3eac12306f6c39bcbf96a65a
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