Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Transformers
Russian
bert
pretraining
russian
fill-mask
embeddings
masked-lm
tiny
feature-extraction
text-embeddings-inference
Instructions to use cointegrated/rubert-tiny2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use cointegrated/rubert-tiny2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cointegrated/rubert-tiny2") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use cointegrated/rubert-tiny2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("cointegrated/rubert-tiny2") model = AutoModelForPreTraining.from_pretrained("cointegrated/rubert-tiny2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tinybert-ru-labse-adapter-v2.pt from cointegrated/rubert-tiny2: direct link, hf CLI and curl.
- Browser
- Download file 963 kB
-
https://huggingface.co/cointegrated/rubert-tiny2/resolve/5add408f84b97f3328f0a29f69561d8cb974e4fe/tinybert-ru-labse-adapter-v2.pt
- Command line
-
hf download hf://cointegrated/rubert-tiny2@5add408f84b97f3328f0a29f69561d8cb974e4fe/tinybert-ru-labse-adapter-v2.pt
-
curl -L -o tinybert-ru-labse-adapter-v2.pt https://huggingface.co/cointegrated/rubert-tiny2/resolve/5add408f84b97f3328f0a29f69561d8cb974e4fe/tinybert-ru-labse-adapter-v2.pt
963 kB
- Xet hash:
- 671ee27c52f0a85dcccdb55178561ea37030b6ae7f55599313ca24079a3a19d9
- Size of remote file:
- 963 kB
- SHA256:
- 3322adeaf437ec8005bd042a64f501458abd5ac58a2eb13f09df5ed9ba59a9af
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