65 lines
2.1 KiB
Python
65 lines
2.1 KiB
Python
from typing import TYPE_CHECKING, Dict
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import gradio as gr
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from llmtuner.extras.constants import METHODS, SUPPORTED_MODELS
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from llmtuner.extras.template import templates
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from llmtuner.webui.common import list_checkpoint, get_model_path, save_config
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from llmtuner.webui.utils import can_quantize
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if TYPE_CHECKING:
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from gradio.components import Component
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def create_top() -> Dict[str, "Component"]:
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available_models = list(SUPPORTED_MODELS.keys()) + ["Custom"]
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with gr.Row():
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lang = gr.Dropdown(choices=["en", "zh"], value="en", scale=1)
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model_name = gr.Dropdown(choices=available_models, scale=3)
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model_path = gr.Textbox(scale=3)
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with gr.Row():
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finetuning_type = gr.Dropdown(choices=METHODS, value="lora", scale=1)
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checkpoints = gr.Dropdown(multiselect=True, scale=5)
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refresh_btn = gr.Button(scale=1)
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with gr.Accordion(label="Advanced config", open=False) as advanced_tab:
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with gr.Row():
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quantization_bit = gr.Dropdown(choices=["None", "8", "4"], value="None", scale=1)
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template = gr.Dropdown(choices=list(templates.keys()), value="default", scale=1)
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source_prefix = gr.Textbox(scale=2)
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lang.change(save_config, [lang, model_name, model_path])
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model_name.change(
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list_checkpoint, [model_name, finetuning_type], [checkpoints]
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).then(
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get_model_path, [model_name], [model_path]
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) # do not save config since the below line will save
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model_path.change(save_config, [lang, model_name, model_path])
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finetuning_type.change(
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list_checkpoint, [model_name, finetuning_type], [checkpoints]
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).then(
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can_quantize, [finetuning_type], [quantization_bit]
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)
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refresh_btn.click(
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list_checkpoint, [model_name, finetuning_type], [checkpoints], queue=False
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)
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return dict(
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lang=lang,
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model_name=model_name,
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model_path=model_path,
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finetuning_type=finetuning_type,
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checkpoints=checkpoints,
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refresh_btn=refresh_btn,
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advanced_tab=advanced_tab,
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quantization_bit=quantization_bit,
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template=template,
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source_prefix=source_prefix
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)
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