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# Copyright (c) ModelScope Contributors. All rights reserved.
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import gradio as gr
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from typing import Type
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from swift.dataset import get_dataset_list
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from ..base import BaseUI
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class Export(BaseUI):
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group = 'llm_export'
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locale_dict = {
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'merge_lora': {
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'label': {
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'zh': '合并LoRA',
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'en': 'Merge LoRA'
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},
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'info': {
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'zh':
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'LoRA合并的路径在填入的checkpoint同级目录,请查看运行时log获取更具体的信息',
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'en':
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'The output path is in the sibling directory as the input checkpoint. '
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'Please refer to the runtime log for more specific information.'
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},
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},
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'device_map': {
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'label': {
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'zh': '合并LoRA使用的device_map',
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'en': 'The device_map when merge-lora'
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},
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'info': {
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'zh': '如果显存不够请填入cpu',
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'en': 'If GPU memory is not enough, fill in cpu'
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},
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},
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'quant_bits': {
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'label': {
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'zh': '量化比特数',
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'en': 'Quantize bits'
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},
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},
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'quant_method': {
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'label': {
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'zh': '量化方法',
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'en': 'Quantize method'
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},
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},
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'quant_n_samples': {
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'label': {
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'zh': '量化集采样数',
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'en': 'Sampled rows from calibration dataset'
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},
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},
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'max_length': {
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'label': {
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'zh': '量化集的max-length',
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'en': 'The quantize sequence length'
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},
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},
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'output_dir': {
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'label': {
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'zh': '输出路径',
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'en': 'Output dir'
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},
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},
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'dataset': {
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'label': {
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'zh': '校准数据集',
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'en': 'Calibration datasets'
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},
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},
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}
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@classmethod
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def do_build_ui(cls, base_tab: Type['BaseUI']):
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with gr.Row():
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gr.Checkbox(elem_id='merge_lora', scale=10)
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gr.Textbox(elem_id='device_map', scale=20)
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with gr.Row():
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gr.Dropdown(elem_id='quant_bits', scale=20)
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gr.Dropdown(elem_id='quant_method', scale=20)
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gr.Textbox(elem_id='quant_n_samples', scale=20)
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gr.Textbox(elem_id='max_length', scale=20)
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with gr.Row():
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gr.Textbox(elem_id='output_dir', scale=20)
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gr.Dropdown(
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elem_id='dataset', multiselect=True, allow_custom_value=True, choices=get_dataset_list(), scale=20)
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