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()