---
license: mit
---

# notus-7b-v1-int8-ov

 * Model creator: [Argilla](https://huggingface.co/argilla)
 * Original model: [notus-7b-v1](https://huggingface.co/argilla/notus-7b-v1)

## Description

This is [notus-7b-v1](https://huggingface.co/argilla/notus-7b-v1) 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**
* sensitivity_metric: **weight_quantization_error**

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 2024.1.0 and higher
* Optimum Intel 1.16.0 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/notus-7b-v1-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).

## 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/argilla/notus-7b-v1).

## 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.