Instructions to use Charangan/MedBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Charangan/MedBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Charangan/MedBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("Charangan/MedBERT") model = AutoModelForPreTraining.from_pretrained("Charangan/MedBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 578052c45a7ae9fe035c75eade3d0e9cbfde99a11b584d37b3bb6225e786006c
- Size of remote file:
- 436 MB
- SHA256:
- ec1621c823ce3c6b942b2ca1208ae0b9d02020f9436b401711dd9794603b053f
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