Instructions to use ajitrajasekharan/biomedical with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ajitrajasekharan/biomedical with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ajitrajasekharan/biomedical")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ajitrajasekharan/biomedical") model = AutoModelForMaskedLM.from_pretrained("ajitrajasekharan/biomedical", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ab131fde19f60d06b4f506ba1395a48656eaeb5f691376ca5de6eb4507d1842
- Size of remote file:
- 1.34 GB
- SHA256:
- 81bddec52f756941e42cc9547cb6426f2875a7744b0a51769d9ce07d08abdad4
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