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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ncbi/MedCPT-Article-Encoder") model = AutoModel.from_pretrained("ncbi/MedCPT-Article-Encoder", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
d05a736
-
Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (9de8685cd4789a21e222b44831b75dc78bf2e039) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>f1acb51
-
Update README.md
1c48abd -
Update README.md
9b5001c
-
Update README.md
2741e26
-
Update README.md
0f5dbc4 -
Update README.md
4a492fb -
Upload tokenizer
337020a -
Upload model
3230917
-
Update LICENSE
c9318e5 -
initial commit
f449516