设计公司的网站详情专业的网站建设费用

参考链接

知乎帖子
B站视频
huggingface 镜像网站（不太全，比如 Qwen/Qwen2.5-VL-7B-Instruct就没有）
huggingface 5种下载方式汇总
通过huggingface-cli下载模型

不一样的部分是预训练权重的下载和demo

首先安装huggingface_hub

pip install -U huggingface_hub

设置镜像

export HF_ENDPOINT=https://hf-mirror.com

windows端需要添加系统变量。

名称：HF_ENDPOINT，值： "https://hf-mirror.com"

然后通过huggingface-cli下载模型，

huggingface-cli download --resume-download  Qwen/Qwen2.5-VL-7B-Instruct --local-dir ./ --local-dir-use-symlinks False --resume-download

参考：通过huggingface-cli下载模型

运行DEMO

加载模型方式

如果希望下载到指定的目录，可以往from_pretrained方法传入cache_dir 参数，如下所示：

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("internlm/internlm2-chat-7b", torch_dtype=torch.float16, trust_remote_code=True, cache_dir='/home/{username}/huggingface').cuda()

运行以下代码

import gradio as gr
from transformers import Qwen2_5_VLForConditionalGeneration, AutoProcessor
from qwen_vl_utils import process_vision_info
import torch# 加载模型和处理器
model = Qwen2_5_VLForConditionalGeneration.from_pretrained("Qwen/Qwen2.5-VL-7B-Instruct", torch_dtype="auto", device_map="auto"
)
processor = AutoProcessor.from_pretrained("Qwen/Qwen2.5-VL-7B-Instruct")def process_image_and_text(image, text_prompt):if image is None:return "请上传一张图片。"# 构建消息格式messages = [{"role": "user","content": [{"type": "image","image": image,  # Gradio将自动处理图片路径},{"type": "text", "text": text_prompt if text_prompt else "Describe this image."},],}]try:# 准备推理输入text = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)image_inputs, video_inputs = process_vision_info(messages)inputs = processor(text=[text],images=image_inputs,videos=video_inputs,padding=True,return_tensors="pt",)inputs = inputs.to(model.device)# 生成输出with torch.no_grad():generated_ids = model.generate(**inputs, max_new_tokens=128)generated_ids_trimmed = [out_ids[len(in_ids):] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)]output_text = processor.batch_decode(generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False)return output_text[0]except Exception as e:return f"处理过程中出现错误: {str(e)}"# 创建Gradio界面
with gr.Blocks() as demo:gr.Markdown("# Qwen2.5-VL 图像理解演示")with gr.Row():with gr.Column():image_input = gr.Image(type="filepath", label="上传图片")text_input = gr.Textbox(placeholder="请输入提示语（如不输入，默认描述图片）", label="提示语")submit_btn = gr.Button("提交")with gr.Column():output = gr.Textbox(label="输出结果")submit_btn.click(fn=process_image_and_text,inputs=[image_input, text_input],outputs=output)gr.Examples(examples=[["path/to/example1.jpg", "这张图片里有什么？"],["path/to/example2.jpg", "描述图中的场景"],],inputs=[image_input, text_input],)# 启动应用
if __name__ == "__main__":demo.launch(share=True)