PerSRV: Personalized Sticker Retrieval with Vision-Language Model
Paper
•
2410.21801
•
Published
PerSRV provides search keywords given a sticker image and prompt. For more information, please see our paper at the end.
from transformers import AutoProcessor, LlavaForConditionalGeneration
from PIL import Image
PROCESSOR_ID = "llava-hf/llava-1.5-7b-hf"
processor = AutoProcessor.from_pretrained(PROCESSOR_ID)
processor.tokenizer.padding_side = "left"
MODEL_ID = "metchee/persrv"
tuned_model = LlavaForConditionalGeneration.from_pretrained(
MODEL_ID,
torch_dtype=torch.float16,
quantization_config=quantization_config,
)
image_path = ""
prompt = f"USER: <image>\n你是个表情包专家,仔细观察、理解图片中的想表达的感觉,把这个感觉转换成关键词。\nASSISTANT:"
image = Image.open(image_path).convert("RGB")
inputs = processor(text=prompt, images=[image], return_tensors="pt").to("cuda")
generated_ids = tuned_model.generate(**inputs, max_new_tokens=MAX_LENGTH)
generated_texts = processor.batch_decode(generated_ids, skip_special_tokens=True)
If you find PerSRV helpful to your research, please cite the following paper :)
@misc{chee2024persrvpersonalizedstickerretrieval,
title={PerSRV: Personalized Sticker Retrieval with Vision-Language Model},
author={Heng Er Metilda Chee and Jiayin Wang and Zhiqiang Guo and Weizhi Ma and Min Zhang},
year={2024},
eprint={2410.21801},
archivePrefix={arXiv},
primaryClass={cs.IR},
url={https://arxiv.org/abs/2410.21801},
}
Base model
llava-hf/llava-1.5-7b-hf