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README.md
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@@ -70,65 +70,6 @@ output = ov_model.generate(**inputs, do_sample=False, max_new_tokens=100, temper
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```
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## Running Model Inference with [OpenVINO GenAI](https://github.com/openvinotoolkit/openvino.genai)
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1. Install packages required for using OpenVINO GenAI.
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```
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pip install --pre -U --extra-index-url https://storage.openvinotoolkit.org/simple/wheels/pre-release openvino openvino-tokenizers openvino-genai
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pip install huggingface_hub
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```
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2. Download model from HuggingFace Hub
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```
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import huggingface_hub as hf_hub
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model_id = "OpenVINO/pixtral-12b-int4-ov"
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model_path = "pixtral-12b-int4-ov"
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hf_hub.snapshot_download(model_id, local_dir=model_path)
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```
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1. Run model inference:
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```
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import openvino_genai as ov_genai
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import requests
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from PIL import Image
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from io import BytesIO
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import numpy as np
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import openvino as ov
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device = "CPU"
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pipe = ov_genai.VLMPipeline(model_path, device)
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def load_image(image_file):
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if isinstance(image_file, str) and (image_file.startswith("http") or image_file.startswith("https")):
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response = requests.get(image_file)
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image = Image.open(BytesIO(response.content)).convert("RGB")
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else:
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image = Image.open(image_file).convert("RGB")
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image_data = np.array(image.getdata()).reshape(1, image.size[1], image.size[0], 3).astype(np.byte)
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return ov.Tensor(image_data)
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prompt = "What is unusual on this picture?"
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url = "https://github.com/openvinotoolkit/openvino_notebooks/assets/29454499/d5fbbd1a-d484-415c-88cb-9986625b7b11"
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image_tensor = load_image(url)
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def streamer(subword: str) -> bool:
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print(subword, end="", flush=True)
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return False
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pipe.start_chat()
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output = pipe.generate(prompt, image=image_tensor, max_new_tokens=100, streamer=streamer)
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pipe.finish_chat()
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```
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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)
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## Limitations
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```
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## Limitations
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