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--- |
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base_model: |
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- OpenGVLab/InternVL2-2B |
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--- |
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This is the [OpenGVLab/InternVL2-2B](https://huggingface.co/OpenGVLab/InternVL2-2B) model, converted to OpenVINO |
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with INT4 compressed weights for the language model, INT8 weights for the other models. |
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Use OpenVINO GenAI 2025.1 or later and Pillow to run inference on this model: |
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- `pip install --upgrade openvino-genai pillow` |
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- Download a test image: `curl -O "https://storage.openvinotoolkit.org/test_data/images/dog.jpg"` |
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- Run inference: |
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```python |
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import numpy as np |
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import openvino as ov |
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import openvino_genai |
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from PIL import Image |
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# Choose GPU instead of CPU in the line below to run the model on Intel integrated or discrete GPU |
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pipe = openvino_genai.VLMPipeline("./InternVL2-2B-ov", "CPU") |
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image = Image.open("dog.jpg") |
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image_data = np.array(image.getdata()).reshape(1, image.size[1], image.size[0], 3).astype(np.uint8) |
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image_data = ov.Tensor(image_data) |
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prompt = "Can you describe the image?" |
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result = pipe.generate(prompt, image=image_data, max_new_tokens=100) |
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print(result.texts[0]) |
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``` |
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See [OpenVINO GenAI repository](https://github.com/openvinotoolkit/openvino.genai?tab=readme-ov-file#performing-visual-language-text-generation) |
