Sentence Similarity
sentence-transformers
Safetensors
English
bidirectional_pplx_qwen3
feature-extraction
RAG
domain-adapted
custom-embeddings
custom_code
text-embeddings-inference
Instructions to use Layasaran/text_embed_0.5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Layasaran/text_embed_0.5b with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Layasaran/text_embed_0.5b", trust_remote_code=True) 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
File size: 284 Bytes
8b90eb3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"__version__": {
"pytorch": "2.11.0+cu128",
"sentence_transformers": "5.6.0",
"transformers": "5.13.1"
},
"default_prompt_name": null,
"model_type": "SentenceTransformer",
"prompts": {
"document": "",
"query": ""
},
"similarity_fn_name": "cosine"
} |