库名称: transformers
任务类型: 图像文本到文本
基础模型:

• Hon-Wong/VoRA-7B-Base
  数据集:
• Hon-Wong/VoRA-Recap-29M

VoRA

• ArXiv论文
• Github

快速开始

该模型可按以下方式使用：

import torch  
from transformers import AutoProcessor, AutoModelForCausalLM  
model_name = "Hon-Wong/VoRA-7B-Instruct"  
processor = AutoProcessor.from_pretrained(model_name, trust_remote_code=True)  
model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True)  
conversation = [  
    {  
        "role":"user",  
        "content":[  
            {  
                "type":"image",  
                "url": "{图片路径或URL}"  
            },  
            {  
                "type":"text",  
                "text":"<image> 描述这张图片。"  
            }  
        ]  
    }  
]  
model_inputs = processor.apply_chat_template(conversation, add_generation_prompt=True, tokenize=True, return_tensors='pt', return_dict=True).to(model.device)  
gen_kwargs = {"max_new_tokens": 1024, "eos_token_id": processor.tokenizer.eos_token_id}  

with torch.inference_mode():  
    outputs = model.generate(model_inputs, **gen_kwargs)  
    output_text = processor.tokenizer.batch_decode(  
        outputs, skip_special_tokens=True  
    )  
    print(output_text)