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add support for downloading and installing LCM lora diffusers models

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This commit is contained in:
Lincoln Stein 2023-11-10 17:38:34 -05:00 committed by Kent Keirsey
parent d7f0a7919f
commit 8702a63197
3 changed files with 20 additions and 10 deletions
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10
invokeai/backend/install/model_install_backend.py
View File

@ -254,7 +254,13 @@ class ModelInstall(object):
elif path.is_dir() and any(
[
(path / x).exists()
for x in {"config.json", "model_index.json", "learned_embeds.bin", "pytorch_lora_weights.bin"}
for x in {
"config.json",
"model_index.json",
"learned_embeds.bin",
"pytorch_lora_weights.bin",
"pytorch_lora_weights.safetensors",
}
]
):
models_installed.update({str(model_path_id_or_url): self._install_path(path)})
@ -357,7 +363,7 @@ class ModelInstall(object):
for suffix in ["safetensors", "bin"]:
if f"{prefix}pytorch_lora_weights.{suffix}" in files:
location = self._download_hf_model(
repo_id, ["pytorch_lora_weights.bin"], staging, subfolder=subfolder
repo_id, [f"pytorch_lora_weights.{suffix}"], staging, subfolder=subfolder
) # LoRA
break
elif (

9
invokeai/backend/model_management/model_probe.py
View File

@ -183,12 +183,13 @@ class ModelProbe(object):
if model:
class_name = model.__class__.__name__
else:
for suffix in ["bin", "safetensors"]:
if (folder_path / f"learned_embeds.{suffix}").exists():
return ModelType.TextualInversion
if (folder_path / f"pytorch_lora_weights.{suffix}").exists():
return ModelType.Lora
if (folder_path / "unet/model.onnx").exists():
return ModelType.ONNX
if (folder_path / "learned_embeds.bin").exists():
return ModelType.TextualInversion
if (folder_path / "pytorch_lora_weights.bin").exists():
return ModelType.Lora
if (folder_path / "image_encoder.txt").exists():
return ModelType.IPAdapter

9
invokeai/backend/model_management/models/lora.py
View File

@ -68,7 +68,8 @@ class LoRAModel(ModelBase):
raise ModelNotFoundException()
if os.path.isdir(path):
if os.path.exists(os.path.join(path, "pytorch_lora_weights.bin")):
for ext in ["safetensors", "bin"]:
if os.path.exists(os.path.join(path, f"pytorch_lora_weights.{ext}")):
return LoRAModelFormat.Diffusers
if os.path.isfile(path):
@ -86,8 +87,10 @@ class LoRAModel(ModelBase):
base_model: BaseModelType,
) -> str:
if cls.detect_format(model_path) == LoRAModelFormat.Diffusers:
# TODO: add diffusers lora when it stabilizes a bit
raise NotImplementedError("Diffusers lora not supported")
for ext in ["safetensors", "bin"]: # return path to the safetensors file inside the folder
path = Path(model_path, f"pytorch_lora_weights.{ext}")
if path.exists():
return path
else:
return model_path