AI/diffusers
1
0
Fork 0
mirror of https://github.com/huggingface/diffusers.git synced 2026-01-29 07:22:12 +03:00
Code Activity

swap embedder location

Browse Source
This commit is contained in:
Edna
2025-06-11 19:04:52 -06:00
committed by GitHub
parent 2fcc75a6d8
commit 0b027a2453
1 changed files with 6 additions and 6 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
src/diffusers/loaders/single_file_utils.py
View File

@@ -3333,20 +3333,20 @@ def convert_chroma_transformer_checkpoint_to_diffusers(checkpoint, **kwargs):
return new_weight
# guidance
converted_state_dict["time_text_embed.embedder.in_proj.bias"] = checkpoint.pop(
converted_state_dict["distilled_guidance_layer.in_proj.bias"] = checkpoint.pop(
"distilled_guidance_layer.in_proj.bias"
)
converted_state_dict["time_text_embed.embedder.in_proj.weight"] = checkpoint.pop(
converted_state_dict["distilled_guidance_layer.in_proj.weight"] = checkpoint.pop(
"distilled_guidance_layer.in_proj.weight"
)
converted_state_dict["time_text_embed.embedder.out_proj.bias"] = checkpoint.pop(
converted_state_dict["distilled_guidance_layer.out_proj.bias"] = checkpoint.pop(
"distilled_guidance_layer.out_proj.bias"
)
converted_state_dict["time_text_embed.embedder.out_proj.weight"] = checkpoint.pop(
converted_state_dict["distilled_guidance_layer.out_proj.weight"] = checkpoint.pop(
"distilled_guidance_layer.out_proj.weight"
)
for i in range(num_guidance_layers):
block_prefix = f"time_text_embed.embedder.layers.{i}."
block_prefix = f"distilled_guidance_layer.layers.{i}."
converted_state_dict[f"{block_prefix}linear_1.bias"] = checkpoint.pop(
f"distilled_guidance_layer.layers.{i}.in_layer.bias"
)
@@ -3359,7 +3359,7 @@ def convert_chroma_transformer_checkpoint_to_diffusers(checkpoint, **kwargs):
converted_state_dict[f"{block_prefix}linear_2.weight"] = checkpoint.pop(
f"distilled_guidance_layer.layers.{i}.out_layer.weight"
)
converted_state_dict[f"time_text_embed.embedder.norms.{i}.weight"] = checkpoint.pop(
converted_state_dict[f"distilled_guidance_layer.norms.{i}.weight"] = checkpoint.pop(
f"distilled_guidance_layer.norms.{i}.scale"
)