Instructions to use ncbi/MedCPT-Article-Encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ncbi/MedCPT-Article-Encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ncbi/MedCPT-Article-Encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ncbi/MedCPT-Article-Encoder") model = AutoModel.from_pretrained("ncbi/MedCPT-Article-Encoder") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 336eae9ed29397831f8d74467b46418def797e332165bc034fd7d85f0991413b
- Size of remote file:
- 438 MB
- SHA256:
- cd871cb879712bac60904311303a08a77bbf2a05cbcac6c7b073c26f1e235914
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