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
| { | |
| "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 | |
| } |