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transformers - ✅(Solved) Fix Liger Kernel is not applied when creating the model with `model_init` [1 pull requests, 3 comments, 2 participants]

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huggingface/transformers#44315•Fetched 2026-04-08 00:29:12
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linfeng-dulinfeng-du
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linfeng-dulinfeng-duSunMarcSunMarc
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Fix Action

Fixed

PR fix notes

PR #44329: Enable Liger Kernel when doing hyperparameter search.

Description (problem / solution / changelog)

What does this PR do?

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Fixes #44315. Check args.use_liger_kernel after it is updated by _hp_search_setup(trial).

Before submitting

  • This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
  • Did you read the contributor guideline, Pull Request section?
  • Was this discussed/approved via a Github issue or the forum? Please add a link to it if that's the case.
  • Did you make sure to update the documentation with your changes? Here are the documentation guidelines, and here are tips on formatting docstrings.
  • Did you write any new necessary tests?

Who can review?

@SunMarc

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Changed files

  • src/transformers/trainer.py (modified, +3/-3)
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System Info

N/A

Who can help?

@SunMarc In Trainer.train, the Liger Kernel is not applied when the model is instantiated via call_model_init. As a result, hyperparameter search runs cannot leverage this kernel for acceleration.

Information

  • The official example scripts
  • My own modified scripts

Tasks

  • An officially supported task in the examples folder (such as GLUE/SQuAD, ...)
  • My own task or dataset (give details below)

Reproduction

N/A

Expected behavior

Liger Kernel should be configurable via args.use_liger_kernel when the model is instantiated via model_init.

extent analysis

Fix Plan

Update Model Instantiation to Apply Liger Kernel

To fix the issue, we need to modify the Trainer.train method to apply the Liger Kernel when the model is instantiated via call_model_init. Here are the concrete steps:

Step 1: Update Trainer Class

class Trainer:
    def train(self, args, model_init):
        # Check if Liger Kernel should be used
        if args.use_liger_kernel:
            # Apply Liger Kernel when model is instantiated via `call_model_init`
            if model_init == 'call_model_init':
                model = LigerKernelModel(model_init())
            else:
                model = model_init()
        else:
            model = model_init()

Step 2: Update LigerKernelModel Class

class LigerKernelModel:
    def __init__(self, model):
        self.model = model
        # Initialize Liger Kernel
        self.liger_kernel = LigerKernel()

Step 3: Update LigerKernel Class

class LigerKernel:
    def __init__(self):
        # Initialize Liger Kernel
        pass

    def apply(self, model):
        # Apply Liger Kernel to the model
        pass

Step 4: Update args to Include use_liger_kernel Flag

args = parser.parse_args()
args.use_liger_kernel = True  # Set flag to True to use Liger Kernel

Verification

To verify that the fix worked, run the hyperparameter search with the use_liger_kernel flag set to True. Check if the Liger Kernel is applied correctly and if the hyperparameter search runs with acceleration.

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FAQ

Expected behavior

Liger Kernel should be configurable via args.use_liger_kernel when the model is instantiated via model_init.

#api#ssr#installation#tensor shape#autograd error#integration issue#index setup#retrieval issue#search optimization#API routing

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transformers - ✅(Solved) Fix Liger Kernel is not applied when creating the model with `model_init` [1 pull requests, 3 comments, 2 participants]