Fill-Mask
Transformers
PyTorch
Safetensors
Russian
English
bert
pretraining
russian
embeddings
masked-lm
tiny
feature-extraction
sentence-similarity
Instructions to use cointegrated/rubert-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cointegrated/rubert-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="cointegrated/rubert-tiny")# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("cointegrated/rubert-tiny") model = AutoModelForPreTraining.from_pretrained("cointegrated/rubert-tiny", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 056debe91f4ec6dc5d1c53c8fd3affb96661f399721ae92d9d60a2ed87bb03d2
- Size of remote file:
- 963 kB
- SHA256:
- 75e6d954d6e9172599b46031ab72c48cdb2a8556a479c4bd94cbb588d6eed4e6
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