| # launch server | |
| # python -m sglang.launch_server --model-path Alibaba-NLP/gme-Qwen2-VL-2B-Instruct --is-embedding | |
| import requests | |
| url = "http://127.0.0.1:30000" | |
| text_input = "Represent this image in embedding space." | |
| image_path = "https://huggingface.co/datasets/liuhaotian/llava-bench-in-the-wild/resolve/main/images/023.jpg" | |
| payload = { | |
| "model": "gme-qwen2-vl", | |
| "input": [{"text": text_input}, {"image": image_path}], | |
| } | |
| response = requests.post(url + "/v1/embeddings", json=payload).json() | |
| print("Embeddings:", [x.get("embedding") for x in response.get("data", [])]) | |