Model Details
Full Model IDmicrosoft/BiomedNLP-BiomedBERT-base-uncased-abstract
Pipeline / Taskfill-mask
Librarytransformers
Downloads (all-time)2.5M
Likes92
Last Modified11/6/2023
Author / Orgmicrosoft
PrivateNo � public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("fill-mask", model="microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract")
# Run inference
result = pipe("Your input here")
print(result)����� Tags
transformerspytorchjaxbertfill-maskexbertenarxiv:2007.15779license:mitendpoints_compatibledeploy:azureregion:us
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This model is designed for the fill-mask task. Explore more models for this use case.
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⬇ Downloads2.5M
����� Community Likes92
🛠�� Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.