Skip to content

Z-Image-Turbo from_single_file fix #12888

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
DN6 merged 1 commit into from
Jan 2, 2026
+9 −5
Merged

Z-Image-Turbo from_single_file fix #12888

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
14 changes: 9 additions & 5 deletions src/diffusers/loaders/single_file_utils.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -120,7 +120,10 @@
"hunyuan-video": "txt_in.individual_token_refiner.blocks.0.adaLN_modulation.1.bias",
"instruct-pix2pix": "model.diffusion_model.input_blocks.0.0.weight",
"lumina2": ["model.diffusion_model.cap_embedder.0.weight", "cap_embedder.0.weight"],
"z-image-turbo": "cap_embedder.0.weight",
"z-image-turbo": [
"model.diffusion_model.layers.0.adaLN_modulation.0.weight",
"layers.0.adaLN_modulation.0.weight",
],
"z-image-turbo-controlnet": "control_all_x_embedder.2-1.weight",
"z-image-turbo-controlnet-2.x": "control_layers.14.adaLN_modulation.0.weight",
"sana": [
Expand Down Expand Up @@ -727,10 +730,7 @@ def infer_diffusers_model_type(checkpoint):
):
model_type = "instruct-pix2pix"

elif (
CHECKPOINT_KEY_NAMES["z-image-turbo"] in checkpoint
and checkpoint[CHECKPOINT_KEY_NAMES["z-image-turbo"]].shape[0] == 2560
):
elif any(key in checkpoint for key in CHECKPOINT_KEY_NAMES["z-image-turbo"]):
model_type = "z-image-turbo"

elif any(key in checkpoint for key in CHECKPOINT_KEY_NAMES["lumina2"]):
Expand Down Expand Up @@ -3852,6 +3852,7 @@ def convert_z_image_transformer_checkpoint_to_diffusers(checkpoint, **kwargs):
".attention.k_norm.weight": ".attention.norm_k.weight",
".attention.q_norm.weight": ".attention.norm_q.weight",
".attention.out.weight": ".attention.to_out.0.weight",
"model.diffusion_model.": "",
}

def convert_z_image_fused_attention(key: str, state_dict: dict[str, object]) -> None:
Expand Down Expand Up @@ -3886,6 +3887,9 @@ def update_state_dict(state_dict: dict[str, object], old_key: str, new_key: str)

update_state_dict(converted_state_dict, key, new_key)

if "norm_final.weight" in converted_state_dict.keys():
_ = converted_state_dict.pop("norm_final.weight")

# Handle any special logic which can't be expressed by a simple 1:1 remapping with the handlers in
# special_keys_remap
for key in list(converted_state_dict.keys()):
Expand Down
Loading