Instructions to use DT4H/CardioBERTa.ro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DT4H/CardioBERTa.ro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="DT4H/CardioBERTa.ro")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("DT4H/CardioBERTa.ro") model = AutoModelForMaskedLM.from_pretrained("DT4H/CardioBERTa.ro", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e5829c8b71ff391fb7b49dd1cb744b0745003759b5cd5daa28b52151a056374
- Size of remote file:
- 1.11 GB
- SHA256:
- 954882316ae8cf6dd4e2c5284cc42fd06f1cb36631848852d331e28dc9fc368d
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