Update README.md

README.md

@@ -3,37 +3,43 @@ license: apache-2.0
 language:
 - en
 ---
+
 # Mixtral-8x7b-Instruct-v0.1-int4-ov
+
  * Model creator: [Mistral AI](https://huggingface.co/mistralai)
  * Original model: [Mixtral 8X7B Instruct v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1)
 
 ## Description
-This is [Mixtral-8x7b-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) model converted to [OpenVINO](https://docs.openvino.ai/2024/home.html) Intermediate Representation (IR) format with INT4 compressed weights using [NNCF](https://github.com/openvinotoolkit/nncf).
 
-## Quantization Configuration
+This is [Mixtral-8x7b-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2024/documentation/openvino-ir-format.html) (Intermediate Representation) format with weights compressed to INT4 by [NNCF](https://github.com/openvinotoolkit/nncf).
 
-Model weights was compressed to INT4 precision using `nncf.compress_weights` with the following parameters:
+## Quantization Parameters
+
+Weight compression was performed using `nncf.compress_weights` with the following parameters:
 
 * mode: **INT4_SYM**
 * group_size: **128**
 * ratio: **0.8**
 
-More details about optimization parameters can be found in [OpenVINO model optimization guide](https://docs.openvino.ai/2024/openvino-workflow/model-optimization-guide/weight-compression.html)
+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
 
-This provided IR is compatible with openvino starting with 2024.0.0 version and optimum-intel 1.16.0
+The provided OpenVINO™ IR model is compatible with:
+
+* OpenVINO version 2024.0.0 and higher
+* Optimum Intel 1.16.0 and higher
 
-## Usage
+## Running Model Inference
 
-### Install required packages
+1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend:
 
-To install the required components for using [Optimum Intel integration](https://huggingface.co/docs/optimum/intel/index) with the OpenVINO backend, do: 
 ```
 pip install optimum[openvino]
 ```
 
-### Run model inference
+2. Run model inference:
+
 ```
 from transformers import AutoTokenizer
 from optimum.intel.openvino import OVModelForCausalLM
@@ -55,8 +61,12 @@ outputs = model.generate(inputs, max_new_tokens=20)
 print(tokenizer.decode(outputs[0], skip_special_tokens=True))
 ```
 
-For more examples and possible optimizations please refer [OpenVINO Large Language Model Inference Guide](https://docs.openvino.ai/2024/learn-openvino/llm_inference_guide.html)
+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 [limitations](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1#limitations).
 
-### Limitations
+## Legal information
 
-Please check original model card for model usage [limitations](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1#limitations)
+The original model is distributed under [Apache 2.0](https://choosealicense.com/licenses/apache-2.0/) license. More details can be found in [original model card](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1).