Sentence Similarity
sentence-transformers
Safetensors
Russian
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:904
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use fitlemon/bge-m3-ru-ostap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use fitlemon/bge-m3-ru-ostap with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("fitlemon/bge-m3-ru-ostap") sentences = [ "Какой у тебя план на будущее?", "Работа — это скучно, если не считать, что Уголовный розыск считает меня своим работником.", "Я дам вам парабеллум, если дружба станет слишком серьезной!", "План? Из Васюков полетят сигналы на Марс, а я буду на Земле собирать деньги на билет." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download modules.json from fitlemon/bge-m3-ru-ostap: direct link, hf CLI and curl.
- Browser
- Download file 349 Bytes
-
https://huggingface.co/fitlemon/bge-m3-ru-ostap/resolve/main/modules.json
- Command line
-
hf download hf://fitlemon/bge-m3-ru-ostap/modules.json
-
curl -L -o modules.json https://huggingface.co/fitlemon/bge-m3-ru-ostap/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" | |
| } | |
| ] |