Sentence Similarity
sentence-transformers
Safetensors
PyTorch
English
qwen3_vl
embeddings
retrieval
semantic-search
multimodal
image-text-retrieval
document-retrieval
Instructions to use Convence/Silas-Embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Convence/Silas-Embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Convence/Silas-Embedding") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "transformer_task": "feature-extraction", | |
| "modality_config": { | |
| "text": { | |
| "method": "forward", | |
| "method_output_name": "last_hidden_state" | |
| }, | |
| "image": { | |
| "method": "forward", | |
| "method_output_name": "last_hidden_state" | |
| }, | |
| "video": { | |
| "method": "forward", | |
| "method_output_name": "last_hidden_state" | |
| }, | |
| "message": { | |
| "method": "forward", | |
| "method_output_name": "last_hidden_state", | |
| "format": "structured" | |
| } | |
| }, | |
| "module_output_name": "token_embeddings", | |
| "processing_kwargs": { | |
| "chat_template": { | |
| "add_generation_prompt": true | |
| } | |
| }, | |
| "unpad_inputs": false | |
| } |