Update README.md

README.md

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 license: apache-2.0
 ---
 
-<!-- Model name used as model card title -->
 # TinyLlama-1.1B-Chat-v1.0-int4-ov
-<!-- Original model reference -->
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  * Model creator: [TinyLlama](https://huggingface.co/TinyLlama)
  * Original model: [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0)
 
-<!-- Description of converted model -->  
 ## Description
 
-<!-- Comment and reference on NNCF applicable only for INT8 and INT4 models -->
 This is [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) 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).
 
 ## Quantization Parameters
 
 Weight compression was performed using `nncf.compress_weights` with the following parameters:
 
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 * mode: **INT4_SYM**
 * group_size: **128**
 * ratio: **1.0**
@@ -34,8 +30,6 @@ The provided OpenVINO™ IR model is compatible with:
 
 ## Running Model Inference
 
-<!-- Example model usage -->
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 1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend:
 
 ```
@@ -44,8 +38,6 @@ pip install optimum[openvino]
 
 2. Run model inference:
 
-<!-- Usage example can be adopted from original model usage example -->
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 ```
 from transformers import AutoTokenizer
 from optimum.intel.openvino import OVModelForCausalLM
@@ -65,7 +57,6 @@ For more examples and possible optimizations, refer to the [OpenVINO Large Langu
 
 ## Legal information
 
-<!-- Note about original model license -->
 The original model is distributed under [apache-2.0](https://choosealicense.com/licenses/apache-2.0/) license. More details can be found in [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0).
 
 ## Disclaimer