Sentence Similarity
sentence-transformers
ONNX
Safetensors
Russian
modernbert
feature-extraction
text-embeddings-inference
Instructions to use Pood666/USER2-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Pood666/USER2-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Pood666/USER2-small") sentences = [ "Это счастливый человек", "Это счастливая собака", "Это очень счастливый человек", "Сегодня солнечный день" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 520 Bytes
c3d3158 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"disable_gelu_fusion": true,
"disable_shape_inference": false,
"disable_attention_fusion": false,
"disable_skip_layer_norm_fusion": false,
"disable_bias_gelu_fusion": false,
"disable_embedlayer_norm_fusion": false,
"disable_bias_skip_layer_norm_fusion": false,
"disable_bias_add_fusion": false,
"disable_layer_norm_fusion": false,
"disable_softmax_fusion": false,
"disable_dropout_fusion": false,
"disable_packed_kv_fusion": false,
"use_raw_attention_mask": false,
"optimization_level": 1
} |