Llava Next Example#

Source vllm-project/vllm.

 1from io import BytesIO
 2
 3import requests
 4from PIL import Image
 5
 6from vllm import LLM, SamplingParams
 7
 8
 9def run_llava_next():
10    llm = LLM(model="llava-hf/llava-v1.6-mistral-7b-hf", max_model_len=4096)
11
12    prompt = "[INST] <image>\nWhat is shown in this image? [/INST]"
13    url = "https://h2o-release.s3.amazonaws.com/h2ogpt/bigben.jpg"
14    image = Image.open(BytesIO(requests.get(url).content))
15    sampling_params = SamplingParams(temperature=0.8,
16                                     top_p=0.95,
17                                     max_tokens=100)
18
19    outputs = llm.generate(
20        {
21            "prompt": prompt,
22            "multi_modal_data": {
23                "image": image
24            }
25        },
26        sampling_params=sampling_params)
27
28    generated_text = ""
29    for o in outputs:
30        generated_text += o.outputs[0].text
31
32    print(f"LLM output:{generated_text}")
33
34
35if __name__ == "__main__":
36    run_llava_next()