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https://git.datalinker.icu/vllm-project/vllm.git
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d9e98f42e4
Signed-off-by: Xiaowei Jiang <xwjiang2010@gmail.com> Co-authored-by: Roger Wang <ywang@roblox.com>
53 lines
1.1 KiB
Python
53 lines
1.1 KiB
Python
import os
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import subprocess
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from PIL import Image
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from vllm import LLM
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# The assets are located at `s3://air-example-data-2/vllm_opensource_llava/`.
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# You can use `.buildkite/download-images.sh` to download them
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def run_llava():
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llm = LLM(model="llava-hf/llava-1.5-7b-hf")
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prompt = "USER: <image>\nWhat is the content of this image?\nASSISTANT:"
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image = Image.open("images/stop_sign.jpg")
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outputs = llm.generate({
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"prompt": prompt,
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"multi_modal_data": {
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"image": image
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},
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})
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for o in outputs:
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generated_text = o.outputs[0].text
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print(generated_text)
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def main():
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run_llava()
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if __name__ == "__main__":
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# Download from s3
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s3_bucket_path = "s3://air-example-data-2/vllm_opensource_llava/"
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local_directory = "images"
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# Make sure the local directory exists or create it
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os.makedirs(local_directory, exist_ok=True)
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# Use AWS CLI to sync the directory, assume anonymous access
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subprocess.check_call([
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"aws",
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"s3",
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"sync",
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s3_bucket_path,
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local_directory,
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"--no-sign-request",
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])
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main()
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