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NeuML
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bert-tiny-sts-last-pooling

Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
dense
Generated from Trainer
loss:CosineSimilarityLoss
text-embeddings-inference
Model card Files
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How to use from the
Use from the
sentence-transformers library
from sentence_transformers import SentenceTransformer

model = SentenceTransformer("NeuML/bert-tiny-sts-last-pooling")

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]

Model Card for BERT Tiny with last token pooling

This model is for testing last token pooling.

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Dataset used to train NeuML/bert-tiny-sts-last-pooling