Sentence Similarity
sentence-transformers
Safetensors
PyTorch
English
qwen3_vl
embeddings
retrieval
semantic-search
multimodal
image-text-retrieval
document-retrieval
Instructions to use Ill-Ness/Silas-Embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Ill-Ness/Silas-Embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Ill-Ness/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
- Xet hash:
- fd0498b050f369b0b10254fe00e8636bb265b71b8690310591a18ac3676d9372
- Size of remote file:
- 11.4 MB
- SHA256:
- 7bbd7da4557f4f46591cf4eec87298afe7a5015f11a8449304b84821f2475d0c
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