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README.md

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+---
+base_model: sentence-transformers/all-mpnet-base-v2
+datasets:
+- s2orc
+- flax-sentence-embeddings/stackexchange_xml
+- ms_marco
+- gooaq
+- yahoo_answers_topics
+- code_search_net
+- search_qa
+- eli5
+- snli
+- multi_nli
+- wikihow
+- natural_questions
+- trivia_qa
+- embedding-data/sentence-compression
+- embedding-data/flickr30k-captions
+- embedding-data/altlex
+- embedding-data/simple-wiki
+- embedding-data/QQP
+- embedding-data/SPECTER
+- embedding-data/PAQ_pairs
+- embedding-data/WikiAnswers
+language: en
+library_name: sentence-transformers
+license: apache-2.0
+pipeline_tag: sentence-similarity
+tags:
+- sentence-transformers
+- feature-extraction
+- sentence-similarity
+- transformers
+- openvino
+- nncf
+- 8-bit
+base_model_relation: quantized
+---
+
+This model is a quantized version of [`sentence-transformers/all-mpnet-base-v2`](https://huggingface.co/sentence-transformers/all-mpnet-base-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).
+First make sure you have `optimum-intel` installed:
+```bash
+pip install optimum[openvino]
+```
+To load your model you can do as follows:
+```python
+from optimum.intel import OVModelForFeatureExtraction
+model_id = "AIFunOver/all-mpnet-base-v2-openvino-8bit"
+model = OVModelForFeatureExtraction.from_pretrained(model_id)
+```