Model Details
Full Model IDmicrosoft/mdeberta-v3-base
Pipeline / Taskfill-mask
Librarytransformers
Downloads (all-time)1.4M
Likes219
Last Modified4/6/2023
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/mdeberta-v3-base")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchtfdeberta-v2debertadeberta-v3mdebertafill-maskmultilingualenarbgdeelesfrhiruswthtrurvizharxiv:2006.03654arxiv:2111.09543license:mitendpoints_compatibledeploy:azureregion:us
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: fill-mask
This model is designed for the fill-mask task. Explore more models for this use case.
All fill-mask Models →📊 Popularity
⬇ Downloads1.4M
❤️ Community Likes219
🛠️ 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.