Update README.md

README.md

@@ -46,91 +46,29 @@ pip install git+https://github.com/huggingface/optimum-intel.git
 from PIL import Image 
 import requests 
 from optimum.intel.openvino import OVModelForVisualCausalLM
-from transformers import AutoTokenizer, TextStreamer
+from transformers import AutoProcessor, TextStreamer
 
-model_id = "OpenVINO/pixtral-12b-int8-ov"
-
-tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
-
-ov_model = OVModelForVisualCausalLM.from_pretrained(model_id, trust_remote_code=True)
-prompt = "What is unusual on this picture?"
-
-url = "https://github.com/openvinotoolkit/openvino_notebooks/assets/29454499/d5fbbd1a-d484-415c-88cb-9986625b7b11"
-image = Image.open(requests.get(url, stream=True).raw)
-
-inputs = ov_model.preprocess_inputs(text=prompt, image=image, tokenizer=tokenizer, config=ov_model.config)
-
-generation_args = { 
-    "max_new_tokens": 100, 
-    "streamer": TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
-} 
-
-generate_ids = ov_model.generate(**inputs, **generation_args)
-
-generate_ids = generate_ids[:, inputs['input_ids'].shape[1]:]
-response = tokenizer.batch_decode(generate_ids, skip_special_tokens=True)[0]
-
-```
-
-## Running Model Inference with [OpenVINO GenAI](https://github.com/openvinotoolkit/openvino.genai)
-
-1. Install packages required for using OpenVINO GenAI.
-```
-pip install --pre -U --extra-index-url https://storage.openvinotoolkit.org/simple/wheels/pre-release openvino openvino-tokenizers openvino-genai
-
-pip install huggingface_hub
-```
-
-2. Download model from HuggingFace Hub
-   
-```
-import huggingface_hub as hf_hub
 
 model_id = "OpenVINO/pixtral-12b-int8-ov"
-model_path = "pixtral-12b-int8-ov"
-
-hf_hub.snapshot_download(model_id, local_dir=model_path)
 
-```
-
-1. Run model inference:
+processor = AutoProcessor.from_pretrained(model_id)
+ov_model = OVModelForVisualCausalLM.from_pretrained(model_id, trust_remote_code=True)
 
-```
-import openvino_genai as ov_genai
-import requests
-from PIL import Image
-from io import BytesIO
-import numpy as np
-import openvino as ov
-
-device = "CPU"
-pipe = ov_genai.VLMPipeline(model_path, device)
-
-def load_image(image_file):
-    if isinstance(image_file, str) and (image_file.startswith("http") or image_file.startswith("https")):
-        response = requests.get(image_file)
-        image = Image.open(BytesIO(response.content)).convert("RGB")
-    else:
-        image = Image.open(image_file).convert("RGB")
-    image_data = np.array(image.getdata()).reshape(1, image.size[1], image.size[0], 3).astype(np.byte)
-    return ov.Tensor(image_data)
-
-prompt = "What is unusual on this picture?"
+question = "What is unusual in this picture?"
+messages = [
+    {"role": "user", "content": [{"type": "text", "content": question}, {"type": "image"}]},
+]
+text = processor.apply_chat_template(messages, add_generation_prompt=True, tokenize=False)
 
 url = "https://github.com/openvinotoolkit/openvino_notebooks/assets/29454499/d5fbbd1a-d484-415c-88cb-9986625b7b11"
-image_tensor = load_image(url)
+raw_image = Image.open(requests.get(url, stream=True).raw)
 
-def streamer(subword: str) -> bool:
-    print(subword, end="", flush=True)
-    return False
+inputs = processor(text=text, images=[raw_image], return_tensors="pt")
+streamer = TextStreamer(processor.tokenizer, skip_prompt=True, skip_special_tokens=True)
 
-pipe.start_chat()
-output = pipe.generate(prompt, image=image_tensor, max_new_tokens=100, streamer=streamer)
-pipe.finish_chat()
-```
-
-More GenAI usage examples can be found in OpenVINO GenAI library [docs](https://github.com/openvinotoolkit/openvino.genai/blob/master/src/README.md) and [samples](https://github.com/openvinotoolkit/openvino.genai?tab=readme-ov-file#openvino-genai-samples)
+output = ov_model.generate(**inputs, do_sample=False, max_new_tokens=100, temperature=None, top_p=None, streamer=streamer)
 
+```
 
 ## Limitations