Instructions to use nlpie/tiny-clinicalbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpie/tiny-clinicalbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nlpie/tiny-clinicalbert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nlpie/tiny-clinicalbert") model = AutoModelForMaskedLM.from_pretrained("nlpie/tiny-clinicalbert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b72fefabea29037b7062f9d579ccaa65977ba8a558fc3eb7a9a436f83fd2bf29
- Size of remote file:
- 55.6 MB
- SHA256:
- b9200290540012db6ce9a2d5ab0c546dd9fd139c7b2d3bff151c15b675b00834
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.