---
title: Phi-3-mini-4k-instruct-int8-ov
canonical_url: "https://www.modelscope.ai/models/OpenVINO/Phi-3-mini-4k-instruct-int8-ov"
md_url: "https://www.modelscope.ai/models/OpenVINO/Phi-3-mini-4k-instruct-int8-ov.md"
repository: OpenVINO/Phi-3-mini-4k-instruct-int8-ov
last_updated: 2026-11-11
license: mit
pipeline_tag: text-generation
tasks:
  - text-generation
model_type:
  - phi3
architectures:
  - Phi3ForCausalLM
base_model:
  - microsoft/Phi-3-mini-4k-instruct
base_model_relation: quantized
library_name:
  - transformer
  - openvino
  - pytorch
frameworks:
  - pytorch
downloads: 254
stars: 0
---

# Phi-3-mini-4k-instruct-int8-ov

> Phi-3-mini-4k-instruct-int8-ov - An open-source model by OpenVINO on ModelScope. Phi-3-mini-4k-instruct-int8-ov Model creator: Microsoft Original model: Phi-3-mini-4k-instruct

OpenVINO/Phi-3-mini-4k-instruct-int8-ov is a text-generation model on ModelScope. licensed under mit. derived from microsoft/Phi-3-mini-4k-instruct.

- **Repository**: OpenVINO/Phi-3-mini-4k-instruct-int8-ov
- **License**: mit
- **Tasks**: text-generation
- **Base model**: microsoft/Phi-3-mini-4k-instruct
- **Downloads**: 254
- **Stars**: 0
- **Last updated**: 2026-11-11

Source: https://www.modelscope.ai/models/OpenVINO/Phi-3-mini-4k-instruct-int8-ov

---

# Phi-3-mini-4k-instruct-int8-ov
* Model creator: [Microsoft](https://huggingface.co/microsoft)
 * Original model: [Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct)

## Description
This is [Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2024/documentation/openvino-ir-format.html) (Intermediate Representation) format with weights compressed to INT8 by [NNCF](https://github.com/openvinotoolkit/nncf).

## Quantization Parameters

Weight compression was performed using `nncf.compress_weights` with the following parameters:

* mode: **int8_asym**
* ratio: **1**

For more information on quantization, check the [OpenVINO model optimization guide](https://docs.openvino.ai/2024/openvino-workflow/model-optimization-guide/weight-compression.html).


## Compatibility

The provided OpenVINO™ IR model is compatible with:

* OpenVINO version 2024.4.0 and higher
* Optimum Intel 1.23.1 and higher

## Running Model Inference

1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend:

```
pip install optimum[openvino]
```

2. Run model inference:

```
from transformers import AutoTokenizer
from optimum.intel.openvino import OVModelForCausalLM

model_id = "OpenVINO/Phi-3-mini-4k-instruct-int8-ov"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = OVModelForCausalLM.from_pretrained(model_id)

inputs = tokenizer("What is OpenVINO?", return_tensors="pt")

outputs = model.generate(**inputs, max_length=200)
text = tokenizer.batch_decode(outputs)[0]
print(text)
```

For more examples and possible optimizations, refer to the [OpenVINO Large Language Model Inference Guide](https://docs.openvino.ai/2024/learn-openvino/llm_inference_guide.html).

## Limitations

Check the original model card for [original model card](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) for limitations.

## Legal information

The original model is distributed under [mit](https://choosealicense.com/licenses/mit/) license. More details can be found in [original model card](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct).

## Disclaimer

Intel is committed to respecting human rights and avoiding causing or contributing to adverse impacts on human rights. See [Intel’s Global Human Rights Principles](https://www.intel.com/content/dam/www/central-libraries/us/en/documents/policy-human-rights.pdf). Intel’s products and software are intended only to be used in applications that do not cause or contribute to adverse impacts on human rights.