Instructions to use alexyalunin/RuBioBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alexyalunin/RuBioBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="alexyalunin/RuBioBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("alexyalunin/RuBioBERT") model = AutoModelForMaskedLM.from_pretrained("alexyalunin/RuBioBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec859a439f10a0aa51ba8a1f7dde20327b8a53517b2edb1f9d6e1ce7829db168
- Size of remote file:
- 714 MB
- SHA256:
- 8cd607296fe10ad37283adde380fb0a1f1948c5b2a80f019bfeccae7523f1619
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.