tocmo0nlord/axolotl
1
0
Fork 0
Code Issues Pull Requests Actions 2 Packages Projects Releases Wiki Activity

upgrade liger and transformers

Browse Source
This commit is contained in:
Wing Lian
2024-11-06 08:53:03 -05:00
parent 1b8d439441
commit 6ac10de9ef
2 changed files with 5 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
requirements.txt
View File

@@ -1,10 +1,10 @@
--extra-index-url https://huggingface.github.io/autogptq-index/whl/cu118/ --extra-index-url https://huggingface.github.io/autogptq-index/whl/cu118/
packaging==23.2 packaging==23.2
peft==0.13.2 peft==0.13.2
transformers==4.46.0 transformers==4.46.2
tokenizers>=0.20.1 tokenizers>=0.20.1
bitsandbytes==0.44.1 bitsandbytes==0.44.1
accelerate==1.0.1 accelerate==1.0.2
datasets==3.0.1 datasets==3.0.1
deepspeed==0.15.3 deepspeed==0.15.3
pydantic==2.6.3 pydantic==2.6.3
@@ -34,7 +34,7 @@ tensorboard
python-dotenv==1.0.1 python-dotenv==1.0.1
autoawq>=0.2.5 autoawq>=0.2.5
triton>=2.3.0 triton>=2.3.0
liger-kernel==0.3.1 liger-kernel==0.4.0
mamba-ssm==1.2.0.post1 mamba-ssm==1.2.0.post1

4
src/axolotl/core/trainer_builder.py
View File

@@ -896,13 +896,13 @@ class AxolotlTrainer(SchedulerMixin, Trainer):
for key, value in metrics.items(): for key, value in metrics.items():
self._stored_metrics[train_eval][key].append(value) self._stored_metrics[train_eval][key].append(value)
def _save_checkpoint(self, model, trial, metrics=None): def _save_checkpoint(self, model, trial):
# make sure the checkpoint dir exists, since trainer is flakey # make sure the checkpoint dir exists, since trainer is flakey
checkpoint_folder = f"{PREFIX_CHECKPOINT_DIR}-{self.state.global_step}" checkpoint_folder = f"{PREFIX_CHECKPOINT_DIR}-{self.state.global_step}"
run_dir = self._get_output_dir(trial=trial) run_dir = self._get_output_dir(trial=trial)
output_dir = os.path.join(run_dir, checkpoint_folder) output_dir = os.path.join(run_dir, checkpoint_folder)
os.makedirs(output_dir, exist_ok=True) os.makedirs(output_dir, exist_ok=True)
return super()._save_checkpoint(model, trial, metrics=metrics) return super()._save_checkpoint(model, trial)
class AxolotlMambaTrainer(AxolotlTrainer): class AxolotlMambaTrainer(AxolotlTrainer):