florian-hoenicke's picture
feat: push custom model
46a57af verified
---
license: apache-2.0
datasets:
- fine-tuned/jinaai_jina-embeddings-v2-base-zh-jinaai_jina-embeddings-v2-base-zh-CM
- allenai/c4
language:
- zh
pipeline_tag: feature-extraction
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
- Health
- Medicine
- Treatment
- Diagnosis
- Therapy
---
This model is a fine-tuned version of [**jinaai/jina-embeddings-v2-base-zh**](https://huggingface.co/jinaai/jina-embeddings-v2-base-zh) designed for the following use case:
medical information search
## 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/jinaai_jina-embeddings-v2-base-zh-jinaai_jina-embeddings-v2-base-zh-CM',
trust_remote_code=True
)
embeddings = model.encode([
'first text to embed',
'second text to embed'
])
print(cos_sim(embeddings[0], embeddings[1]))
```