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sidbrahim/narrativesAnalogues-MPNet
narrativesAnalogues-MPNet is a sentence similarity model from sidbrahim. Use it when you need a score for how close two texts are. It is set up for sentence-transformers.
Downloads · 30 days
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.safetensors876 MB · 50%
From the Hugging Face model README
loss: 1.084230661392212
validation_pearson_cosine: 0.8520244193617519
validation_spearman_cosine: 0.7196384923568855
runtime: 144.6206
samples_per_second: 1.328
steps_per_second: 0.083
: 3.0
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)