7a4388c928
在模型管理页面中新增保存模式选择功能，用户可以通过下拉菜单选择不同的保存模式（如默认、合并16位、合并4位等）。同时，将保存模型的逻辑抽离到独立的`save_model.py`文件中，以提高代码的可维护性和复用性。
103 lines
4.5 KiB
Python
103 lines
4.5 KiB
Python
import gradio as gr
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import os # 导入os模块以便扫描文件夹
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import sys
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from pathlib import Path
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from unsloth import FastLanguageModel
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import torch
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sys.path.append(str(Path(__file__).resolve().parent.parent))
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from global_var import get_model, get_tokenizer, set_model, set_tokenizer
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from train import get_model_name
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def model_manage_page():
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workdir = "workdir" # 假设workdir是当前工作目录下的一个文件夹
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models_dir = os.path.join(workdir, "models")
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model_folders = [name for name in os.listdir(models_dir) if os.path.isdir(os.path.join(models_dir, name))] # 扫描models文件夹下的所有子文件夹
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with gr.Blocks() as demo:
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gr.Markdown("## 模型管理")
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state_output = gr.Label(label="当前状态",value="当前未加载模型") # 将 Textbox 改为 Label
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with gr.Row():
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with gr.Column(scale=3):
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model_select_dropdown = gr.Dropdown(choices=model_folders, label="选择模型", interactive=True) # 将子文件夹列表添加到Dropdown组件中，并设置为可选
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max_seq_length_input = gr.Number(label="最大序列长度", value=4096, precision=0)
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load_in_4bit_input = gr.Checkbox(label="使用4位量化", value=True)
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with gr.Column(scale=1):
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load_button = gr.Button("加载模型", variant="primary")
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unload_button = gr.Button("卸载模型", variant="stop")
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refresh_button = gr.Button("刷新模型列表", variant="secondary") # 新增刷新按钮
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with gr.Row():
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with gr.Column(scale=3):
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save_model_name_input = gr.Textbox(label="保存模型名称", placeholder="输入模型保存名称")
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save_method_dropdown = gr.Dropdown(
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choices=["default", "merged_16bit", "merged_4bit", "lora", "gguf", "gguf_q4_k_m", "gguf_f16"],
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label="保存模式",
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value="default"
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)
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with gr.Column(scale=1):
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save_button = gr.Button("保存模型", variant="secondary")
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def load_model(selected_model, max_seq_length, load_in_4bit):
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try:
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# 判空操作，如果模型已加载，则先卸载
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if get_model() is not None:
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unload_model()
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model_path = os.path.join(models_dir, selected_model)
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model, tokenizer = FastLanguageModel.from_pretrained(
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model_name=model_path,
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max_seq_length=max_seq_length,
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load_in_4bit=load_in_4bit,
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)
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set_model(model)
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set_tokenizer(tokenizer)
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return f"模型 {get_model_name(model)} 已加载"
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except Exception as e:
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return f"加载模型时出错: {str(e)}"
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load_button.click(fn=load_model, inputs=[model_select_dropdown, max_seq_length_input, load_in_4bit_input], outputs=state_output)
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def unload_model():
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try:
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# 将模型移动到 CPU
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model = get_model()
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if model is not None:
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model.cpu()
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# 清空 CUDA 缓存
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torch.cuda.empty_cache()
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# 将模型和tokenizer设置为 None
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set_model(None)
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set_tokenizer(None)
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return "当前未加载模型"
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except Exception as e:
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return f"卸载模型时出错: {str(e)}"
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unload_button.click(fn=unload_model, inputs=None, outputs=state_output)
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from train.save_model import save_model_to_dir
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def save_model(save_model_name, save_method):
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return save_model_to_dir(save_model_name, models_dir, get_model(), get_tokenizer(), save_method)
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save_button.click(fn=save_model, inputs=[save_model_name_input, save_method_dropdown], outputs=state_output)
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def refresh_model_list():
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try:
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nonlocal model_folders
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model_folders = [name for name in os.listdir(models_dir) if os.path.isdir(os.path.join(models_dir, name))]
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return gr.Dropdown(choices=model_folders)
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except Exception as e:
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return f"刷新模型列表时出错: {str(e)}"
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refresh_button.click(fn=refresh_model_list, inputs=None, outputs=model_select_dropdown)
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return demo
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if __name__ == "__main__":
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demo = model_manage_page()
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demo.queue()
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demo.launch() |