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--- |
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base_model: |
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- microsoft/Phi-3.5-vision-instruct |
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--- |
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This is the [microsoft/Phi-3.5-vision-instruct](https://huggingface.co/microsoft/Phi-3.5-vision-instruct) model, converted to OpenVINO, with fp16 weights. |
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Use OpenVINO GenAI to run inference on this model: |
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- Install OpenVINO GenAI nightly and pillow: |
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``` |
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pip install --upgrade --pre pillow openvino-genai openvino openvino-tokenizers --extra-index-url https://storage.openvinotoolkit.org/simple/wheels/nightly |
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``` |
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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("Phi-3.5-vision-instruct-ov-fp16", "CPU") |
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pipe.start_chat() |
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# Setting eos_token_id to tokenizer's eos token id is necessary for Phi-3.5-vision-instruct |
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config = openvino_genai.GenerationConfig() |
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config.set_eos_token_id(pipe.get_tokenizer().get_eos_token_id()) |
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config.max_new_tokens = 100 |
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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, generation_config=config) |
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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) |
