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--- |
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license: apache-2.0 |
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datasets: |
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- fine-tuned/jinaai_jina-embeddings-v2-base-en-jinaai_jina-embeddings-v2-base-en-sc |
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- allenai/c4 |
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language: |
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- en |
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pipeline_tag: feature-extraction |
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tags: |
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- sentence-transformers |
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- feature-extraction |
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- sentence-similarity |
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- mteb |
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- Science |
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- Research |
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- Academia |
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- Innovation |
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- Technology |
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--- |
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This model is a fine-tuned version of [**jinaai/jina-embeddings-v2-base-en**](https://huggingface.co/jinaai/jina-embeddings-v2-base-en) designed for the following use case: |
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academic search for scientific papers |
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## How to Use |
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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: |
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```python |
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from sentence_transformers import SentenceTransformer |
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from sentence_transformers.util import cos_sim |
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model = SentenceTransformer( |
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'fine-tuned/jinaai_jina-embeddings-v2-base-en-jinaai_jina-embeddings-v2-base-en-sc', |
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trust_remote_code=True |
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) |
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embeddings = model.encode([ |
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'first text to embed', |
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'second text to embed' |
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]) |
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print(cos_sim(embeddings[0], embeddings[1])) |
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``` |
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