Add finetune stop pause resume finetune_cost finetune_progress multi-gpu training and enhance model infer logic etc. #889
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added 4 commits
December 1, 2025 11:19
Contributor
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support stages: sft, pt, dpo |
Collaborator
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PR描述需要补充完整。 |
Collaborator
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本地验证了两个llamafactory的测试，纯语言模型+多模态模型，训练和推理都正常。 |
JingofXin
reviewed
Dec 18, 2025
wzh1994
reviewed
Dec 18, 2025
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| lazyllm.config.add('trainable_module_config_map_path', str, '', 'TRAINABLE_MODULE_CONFIG_MAP_PATH', | ||
| description='The default path for trainable module config map.') | ||
| lazyllm.config.add( |
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| kw = kw or self._get_train_or_deploy_args(mode, disable=['base_model', 'target_path']) | ||
| # Get default args and merge with user-provided kw, with kw taking precedence | ||
| default_args = self._get_train_or_deploy_args(mode, disable=['base_model', 'target_path']) |
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这里会改变原来的逻辑，正常情况下是用户传kw，就完全使用用户给的；否则使用默认的；现在行为变成了合并参数，即用户传入的覆盖默认的。
这个kw主要用于_async_finetune，其余场景都没用上，需要确认一下_async_finetune场景这样做是否符合预期
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自测时发现不同微调场景用户可能只会传部分参数，但还有些参数是必须的。所以改成了当前逻辑，即优先使用用户传的参数+其它用户没传又需要的参数（使用默认值）。
| kw = kw or self._get_train_or_deploy_args(mode, disable=['base_model', 'target_path']) | ||
| # Get default args and merge with user-provided kw, with kw taking precedence | ||
| default_args = self._get_train_or_deploy_args(mode, disable=['base_model', 'target_path']) | ||
| if kw: |
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kw = {**default_args, **kw} if kw else default_args
Collaborator
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PR描述中，没涉及的内容要清除掉。 |
JingofXin
reviewed
Dec 23, 2025
JingofXin
approved these changes
Dec 29, 2025
suncade
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suncade
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📌 PR 内容 / PR Description
/v1/finetuneTasks/{job_id}:pause和/v1/finetuneTasks/{job_id}:resumeAPI 接口✅ 变更类型 / Type of Change