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: 429 Bytes
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"type": "sentence_transformers.sentence_transformer.modules.pooling.Pooling"
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