upgrade liger and transformers
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@@ -1,10 +1,10 @@
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--extra-index-url https://huggingface.github.io/autogptq-index/whl/cu118/
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packaging==23.2
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peft==0.13.2
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transformers==4.46.0
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transformers==4.46.2
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tokenizers>=0.20.1
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bitsandbytes==0.44.1
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accelerate==1.0.1
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accelerate==1.0.2
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datasets==3.0.1
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deepspeed==0.15.3
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pydantic==2.6.3
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@@ -34,7 +34,7 @@ tensorboard
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python-dotenv==1.0.1
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autoawq>=0.2.5
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triton>=2.3.0
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liger-kernel==0.3.1
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liger-kernel==0.4.0
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mamba-ssm==1.2.0.post1
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@@ -896,13 +896,13 @@ class AxolotlTrainer(SchedulerMixin, Trainer):
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for key, value in metrics.items():
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self._stored_metrics[train_eval][key].append(value)
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def _save_checkpoint(self, model, trial, metrics=None):
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def _save_checkpoint(self, model, trial):
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# make sure the checkpoint dir exists, since trainer is flakey
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checkpoint_folder = f"{PREFIX_CHECKPOINT_DIR}-{self.state.global_step}"
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run_dir = self._get_output_dir(trial=trial)
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output_dir = os.path.join(run_dir, checkpoint_folder)
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os.makedirs(output_dir, exist_ok=True)
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return super()._save_checkpoint(model, trial, metrics=metrics)
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return super()._save_checkpoint(model, trial)
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class AxolotlMambaTrainer(AxolotlTrainer):
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