Sentence Similarity
sentence-transformers
Safetensors
PEFT
English
text-embeddings
retrieval
web-search
news
Instructions to use desearch/Desearch-Embedding-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use desearch/Desearch-Embedding-4B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("desearch/Desearch-Embedding-4B") 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] - PEFT
How to use desearch/Desearch-Embedding-4B with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
File size: 376 Bytes
e82acef | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"__version__": {
"pytorch": "2.13.0+cu130",
"sentence_transformers": "5.7.0",
"transformers": "5.15.0"
},
"default_prompt_name": null,
"model_type": "SentenceTransformer",
"prompts": {
"document": "",
"query": "Instruct: Given a web search query, retrieve relevant passages that answer the query\nQuery:"
},
"similarity_fn_name": "cosine"
} |