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README.md
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---
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base_model: sentence-transformers/all-MiniLM-L6-v2
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datasets:
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- s2orc
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- flax-sentence-embeddings/stackexchange_xml
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- ms_marco
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- gooaq
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- yahoo_answers_topics
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- code_search_net
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- search_qa
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- eli5
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- snli
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- multi_nli
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- wikihow
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- natural_questions
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- trivia_qa
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- embedding-data/sentence-compression
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- embedding-data/flickr30k-captions
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- embedding-data/altlex
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- embedding-data/simple-wiki
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- embedding-data/QQP
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- embedding-data/SPECTER
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- embedding-data/PAQ_pairs
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- embedding-data/WikiAnswers
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language: en
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library_name: sentence-transformers
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license: apache-2.0
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pipeline_tag: sentence-similarity
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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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- transformers
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- openvino
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- nncf
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- 8-bit
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base_model_relation: quantized
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---
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This model is a quantized version of [`sentence-transformers/all-MiniLM-L6-v2`](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) and is converted to the OpenVINO format. This model was obtained via the [nncf-quantization](https://huggingface.co/spaces/echarlaix/nncf-quantization) space with [optimum-intel](https://github.com/huggingface/optimum-intel).
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First make sure you have `optimum-intel` installed:
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```bash
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pip install optimum[openvino]
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```
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To load your model you can do as follows:
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```python
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from optimum.intel import OVModelForFeatureExtraction
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model_id = "AIFunOver/all-MiniLM-L6-v2-openvino-8bit"
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model = OVModelForFeatureExtraction.from_pretrained(model_id)
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```
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