ruSciBERT
Model was trained by Sber AI team and MLSA Lab of Institute for AI, MSU. If you use our model for your project, please tell us about it (nikgerasimenko@gmail.com).
Presentation at the AI Journey 2022
- Task:
mask filling - Type:
encoder - Tokenizer:
bpe - Dict size:
50265 - Num Parameters:
123 M - Training Data Volume:
6.5 GB
- Downloads last month
- 30
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.