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feat: push custom model
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---
license: apache-2.0
datasets:
- fine-tuned/NFCorpus-256-24-gpt-4o-2024-05-13-546049
- allenai/c4
language:
- en
pipeline_tag: feature-extraction
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
- Medical
- Nutrition
- Queries
- Documents
- Relevance
---
This model is a fine-tuned version of [**BAAI/bge-m3**](https://huggingface.co/BAAI/bge-m3) designed for the following use case:
medical information retrieval
## 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:
```python
from sentence_transformers import SentenceTransformer
from sentence_transformers.util import cos_sim
model = SentenceTransformer(
'fine-tuned/NFCorpus-256-24-gpt-4o-2024-05-13-546049',
trust_remote_code=True
)
embeddings = model.encode([
'first text to embed',
'second text to embed'
])
print(cos_sim(embeddings[0], embeddings[1]))
```