Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Transformers
Russian
English
roberta
feature-extraction
russian
fill-mask
pretraining
embeddings
masked-lm
tiny
text-embeddings-inference
Instructions to use mlsa-iai-msu-lab/sci-rus-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mlsa-iai-msu-lab/sci-rus-tiny with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mlsa-iai-msu-lab/sci-rus-tiny") 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 mlsa-iai-msu-lab/sci-rus-tiny with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("mlsa-iai-msu-lab/sci-rus-tiny") model = AutoModel.from_pretrained("mlsa-iai-msu-lab/sci-rus-tiny", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download modules.json from mlsa-iai-msu-lab/sci-rus-tiny: direct link, hf CLI and curl.
- Browser
- Download file 349 Bytes
-
https://huggingface.co/mlsa-iai-msu-lab/sci-rus-tiny/resolve/main/modules.json
- Command line
-
hf download hf://mlsa-iai-msu-lab/sci-rus-tiny/modules.json
-
curl -L -o modules.json https://huggingface.co/mlsa-iai-msu-lab/sci-rus-tiny/resolve/main/modules.json
349 Bytes
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.models.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.models.Pooling" | |
| }, | |
| { | |
| "idx": 2, | |
| "name": "2", | |
| "path": "2_Normalize", | |
| "type": "sentence_transformers.models.Normalize" | |
| } | |
| ] |