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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
- fp16
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: optimized
---
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-fp16"
model = OVModelForCausalLM.from_pretrained(model_id)
```