storytold/FineTrainers-Conditioning
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replaced the pipeline functions.

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time to test this then test the weight changes.
This commit is contained in:
CrossProduct
2025-01-21 02:22:35 +00:00
parent 48d2b61029
commit 34996c1eb1
3 changed files with 26 additions and 15 deletions
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finetrainers/conditioning/LTXVideoConditionedTransformer3DModel.py
+10 -14
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@@ -36,7 +36,6 @@ class LTXVideoConditionedTransformer3DModel(LTXVideoTransformer3DModel):
adapter_dropout=0.1,
adapter_init_scale=1e-3
)
self.adapter.requires_grad_(True)
super().__init__(
in_channels=in_channels,
@@ -59,24 +58,21 @@ class LTXVideoConditionedTransformer3DModel(LTXVideoTransformer3DModel):
@classmethod
def from_pretrained(cls, pretrained_model_name_or_path, **kwargs):
model = super().from_pretrained(pretrained_model_name_or_path, **kwargs)
# model is now a LTXVideoTransformer3DModel instance;
# but we want an instance of LTXVideoTransformer3DModelWithAdapter
# so we often do something like:
new_model = cls(**model.config.__dict__)
new_model.load_state_dict(model.state_dict())
return new_model
def save_pretrained(self, save_directory: str, **kwargs):
"""
Saves model weights (including adapter) + config to disk
in a format compatible with .from_pretrained()
"""
# 1) Save config
self.config.save_pretrained(save_directory)
# def save_pretrained(self, save_directory: str, **kwargs):
# """
# Saves model weights (including adapter) + config to disk
# in a format compatible with .from_pretrained()
# """
# # 1) Save config
# self.config.save_pretrained(save_directory)
# 2) Save PyTorch state dict
state_dict = self.state_dict()
torch.save(state_dict, os.path.join(save_directory, "pytorch_model.bin"))
# # 2) Save PyTorch state dict
# state_dict = self.state_dict()
# torch.save(state_dict, os.path.join(save_directory, "pytorch_model.bin"))
def forward(
self,