Upload README.md

README.md

@@ -56,38 +56,38 @@ Finally, an INT8 quantized version of the Imange Enconder only can be find as op
 
 I suggest to install requirements into a dedicated python-virtualenv or a conda enviroment. 
 
-'''
+```
 pip install -q "torch>=2.1" "torchvision" "Pillow" "tqdm" "datasets>=2.14.6" "gradio>=4.36" "nncf>=2.13.0" --extra-index-url https://download.pytorch.org/whl/cpu
 
 pip install -q "transformers>=4.45" --extra-index-url https://download.pytorch.org/whl/cpu
 
 pip install -Uq --pre "openvino>2024.4.0" --extra-index-url https://storage.openvinotoolkit.org/simple/wheels/nightly
-'''
+```
 
 ### Step 2 Convert the model in OpenVINO Intermediate Representation (IR)
 
-'''
+```
 from pathlib import Path
 from ov_mllama_helper import convert_mllama
 model_id = "meta-llama/Llama-3.2-11B-Vision-Instruct"
 model_dir = Path(model_id.split("/")[-1]) / "OpenVino"
 convert_mllama(model_id, model_dir)
-'''
+```
 
 ### Step 3 INT4 Compression
 
-'''
+```
 from ov_mllama_compression import compress
 from ov_mllama_compression import compression_widgets_helper
 compression_scenario, compress_args = compression_widgets_helper()
 compression_scenario
 compression_kwargs = {key: value.value for key, value in compress_args.items()}
 language_model_path = compress(model_dir, **compression_kwargs)
-'''
+```
 
 ### Step 4 INT8 Image Enconder Optimization
 
-'''
+```
 from ov_mllama_compression import vision_encoder_selection_widget
 vision_encoder_options = vision_encoder_selection_widget(device.value)
 vision_encoder_options
@@ -117,7 +117,7 @@ del calibration_dataset
 del calibration_data
 gc.collect()
 vision_encoder_path = int8_vision_encoder_path
-'''
+```
 
 ## License