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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nlpie/tiny-clinicalbert") model = AutoModelForMaskedLM.from_pretrained("nlpie/tiny-clinicalbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nlpie/tiny-clinicalbert: direct link, hf CLI and curl.
- Browser
- Download file 55.6 MB
-
https://huggingface.co/nlpie/tiny-clinicalbert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nlpie/tiny-clinicalbert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nlpie/tiny-clinicalbert/resolve/main/pytorch_model.bin
55.6 MB
- Xet hash:
- b72fefabea29037b7062f9d579ccaa65977ba8a558fc3eb7a9a436f83fd2bf29
- Size of remote file:
- 55.6 MB
- SHA256:
- b9200290540012db6ce9a2d5ab0c546dd9fd139c7b2d3bff151c15b675b00834
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