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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff253edb10bcb8a0d6e6b0c7de69a5ae392ac8ed74424c1081ca29f5d05349ff
- Size of remote file:
- 55.6 MB
- SHA256:
- c85fb3e6af71cfacb21a0512076b169d8d47effb013c6998398f0026c51c7381
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