Sentence Similarity
sentence-transformers
ONNX
Safetensors
feature-extraction
Generated from Trainer
dataset_size:62698210
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results
Instructions to use sentence-transformers/static-similarity-mrl-multilingual-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sentence-transformers/static-similarity-mrl-multilingual-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/static-similarity-mrl-multilingual-v1") sentences = [ "A man is jumping unto his filthy bed.", "A man is ouside near the beach.", "The bed is dirty.", "The man is on the moon." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Update usage snippet to use organization name
Browse files
README.md
CHANGED
|
@@ -225,7 +225,7 @@ Notably, a lower dimensionality allows for much faster downstream tasks, such as
|
|
| 225 |
```python
|
| 226 |
from sentence_transformers import SentenceTransformer
|
| 227 |
|
| 228 |
-
model = SentenceTransformer("
|
| 229 |
embeddings = model.encode([
|
| 230 |
"I used to hate him.",
|
| 231 |
"Раньше я ненавидел его."
|
|
|
|
| 225 |
```python
|
| 226 |
from sentence_transformers import SentenceTransformer
|
| 227 |
|
| 228 |
+
model = SentenceTransformer("sentence-transformers/static-similarity-mrl-multilingual-v1", truncate_dim=256)
|
| 229 |
embeddings = model.encode([
|
| 230 |
"I used to hate him.",
|
| 231 |
"Раньше я ненавидел его."
|