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README.md

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+---
+base_model: microsoft/Phi-3.5-mini-instruct
+language:
+- multilingual
+library_name: transformers
+license: mit
+license_link: https://huggingface.co/microsoft/Phi-3.5-mini-instruct/resolve/main/LICENSE
+pipeline_tag: text-generation
+tags:
+- nlp
+- code
+- openvino
+- nncf
+- 4-bit
+widget:
+- messages:
+  - role: user
+    content: Can you provide ways to eat combinations of bananas and dragonfruits?
+---
+
+---
+license: mit
+license_link: https://choosealicense.com/licenses/mit/
+base_model:
+- microsoft/Phi-3.5-mini-instruct
+base_model_relation: quantized
+---
+This model is a quantized version of [`microsoft/Phi-3.5-mini-instruct`](https://huggingface.co/microsoft/Phi-3.5-mini-instruct) 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 OVModelForCausalLM
+model_id = "AlexKoff88/Phi-3.5-mini-instruct-openvino-4bit"
+model = OVModelForCausalLM.from_pretrained(model_id)
+```