README.md

---
base_model: microsoft/Phi-3-mini-4k-instruct
language:
- en
license: mit
license_link: https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/LICENSE
pipeline_tag: text-generation
tags:
- nlp
- code
- openvino
- nncf
- 4-bit
inference:
  parameters:
    temperature: 0.0
widget:
- messages:
  - role: user
    content: Can you provide ways to eat combinations of bananas and dragonfruits?
---

This model is a quantized version of [`microsoft/Phi-3-mini-4k-instruct`](https://huggingface.co/microsoft/Phi-3-mini-4k-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 = "emmacall/Phi-3-mini-4k-instruct-openvino-4bit"
model = OVModelForCausalLM.from_pretrained(model_id)
```