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This model is a fine-tuned version of BAAI/bge-m3 designed for the following use case:

general domain

How to Use

This model can be easily integrated into your NLP pipeline for tasks such as text classification, sentiment analysis, entity recognition, and more. Here's a simple example to get you started:

from sentence_transformers import SentenceTransformer
from sentence_transformers.util import cos_sim

model = SentenceTransformer(
    'fine-tuned/BAAI_bge-m3-26062024-gdon-webapp',
    trust_remote_code=True
)

embeddings = model.encode([
    'first text to embed',
    'second text to embed'
])
print(cos_sim(embeddings[0], embeddings[1]))
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Model size
568M params
Tensor type
F32
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Datasets used to train fine-tuned/BAAI_bge-m3-26062024-gdon-webapp

Spaces using fine-tuned/BAAI_bge-m3-26062024-gdon-webapp 2