ros/LLaMA-Factory
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better llamaboard

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* easily resume from checkpoint
* support full and freeze checkpoints
* faster ui


Former-commit-id: 84cfb2452cc86b037ccddee6e833f8eb7c129fa4
This commit is contained in:
hiyouga
2024-05-29 23:55:38 +08:00
parent f90c4ca672
commit 87aa332583
14 changed files with 303 additions and 193 deletions
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23
src/llamafactory/webui/components/top.py
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@@ -3,7 +3,7 @@ from typing import TYPE_CHECKING, Dict
from ...data import templates
from ...extras.constants import METHODS, SUPPORTED_MODELS
from ...extras.packages import is_gradio_available
from ..common import get_model_path, get_template, get_visual, list_adapters, save_config
from ..common import get_model_info, list_checkpoints, save_config
from ..utils import can_quantize
@@ -25,8 +25,7 @@ def create_top() -> Dict[str, "Component"]:
with gr.Row():
finetuning_type = gr.Dropdown(choices=METHODS, value="lora", scale=1)
adapter_path = gr.Dropdown(multiselect=True, allow_custom_value=True, scale=5)
refresh_btn = gr.Button(scale=1)
checkpoint_path = gr.Dropdown(multiselect=True, allow_custom_value=True, scale=6)
with gr.Accordion(open=False) as advanced_tab:
with gr.Row():
@@ -36,27 +35,17 @@ def create_top() -> Dict[str, "Component"]:
booster = gr.Radio(choices=["none", "flashattn2", "unsloth"], value="none", scale=3)
visual_inputs = gr.Checkbox(scale=1)
model_name.change(list_adapters, [model_name, finetuning_type], [adapter_path], queue=False).then(
get_model_path, [model_name], [model_path], queue=False
).then(get_template, [model_name], [template], queue=False).then(
get_visual, [model_name], [visual_inputs], queue=False
) # do not save config since the below line will save
model_name.change(get_model_info, [model_name], [model_path, template, visual_inputs], queue=False)
model_path.change(save_config, inputs=[lang, model_name, model_path], queue=False)
finetuning_type.change(list_adapters, [model_name, finetuning_type], [adapter_path], queue=False).then(
can_quantize, [finetuning_type], [quantization_bit], queue=False
)
refresh_btn.click(list_adapters, [model_name, finetuning_type], [adapter_path], queue=False)
finetuning_type.change(can_quantize, [finetuning_type], [quantization_bit], queue=False)
checkpoint_path.focus(list_checkpoints, [model_name, finetuning_type], [checkpoint_path], queue=False)
return dict(
lang=lang,
model_name=model_name,
model_path=model_path,
finetuning_type=finetuning_type,
adapter_path=adapter_path,
refresh_btn=refresh_btn,
checkpoint_path=checkpoint_path,
advanced_tab=advanced_tab,
quantization_bit=quantization_bit,
template=template,