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:
- 5679d9484dc10ead6a3503c6d28590817e287fb89c4f4154408f24a8723bae43
- Size of remote file:
- 438 MB
- SHA256:
- a5d5ffe4d8666c1d0aa15f371b94fc3492ca8f927e5621abd4b3ee9fc845b0f3
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