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avemio-digital/GRAG-BGE-M3-Pairs-Triples-Hessian-AI
GRAG-BGE-M3-Pairs-Triples-Hessian-AI is a sentence similarity model from avemio-digital. Use it when you need a score for how close two texts are. It is set up for sentence-transformers.
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.safetensors2.3 GB · 99%
From the Hugging Face model README
No validation metrics available
First install the Sentence Transformers library:
pip install -U sentence-transformers
Then you can load this model and run inference.
from sentence_transformers import SentenceTransformer
# Download from the Hugging Face Hub
model = SentenceTransformer("sentence_transformers_model_id")
# Run inference
sentences = [
'search_query: autotrain',
'search_query: auto train',
'search_query: i love autotrain',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)