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update model loader

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This commit is contained in:
Artiprocher
2024-10-08 16:46:44 +08:00
parent 892f80c265
commit ec352cfce2
4 changed files with 189 additions and 90 deletions
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diffsynth/configs/model_config.py
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@@ -353,47 +353,67 @@ preset_models_on_modelscope = {
("Damo_XR_Lab/cv_rife_video-frame-interpolation", "flownet.pkl", "models/RIFE"),
],
# Qwen Prompt
"QwenPrompt": [
("qwen/Qwen2-1.5B-Instruct", "config.json", "models/QwenPrompt/qwen2-1.5b-instruct"),
("qwen/Qwen2-1.5B-Instruct", "generation_config.json", "models/QwenPrompt/qwen2-1.5b-instruct"),
("qwen/Qwen2-1.5B-Instruct", "model.safetensors", "models/QwenPrompt/qwen2-1.5b-instruct"),
("qwen/Qwen2-1.5B-Instruct", "special_tokens_map.json", "models/QwenPrompt/qwen2-1.5b-instruct"),
("qwen/Qwen2-1.5B-Instruct", "tokenizer.json", "models/QwenPrompt/qwen2-1.5b-instruct"),
("qwen/Qwen2-1.5B-Instruct", "tokenizer_config.json", "models/QwenPrompt/qwen2-1.5b-instruct"),
("qwen/Qwen2-1.5B-Instruct", "merges.txt", "models/QwenPrompt/qwen2-1.5b-instruct"),
("qwen/Qwen2-1.5B-Instruct", "vocab.json", "models/QwenPrompt/qwen2-1.5b-instruct"),
],
"QwenPrompt": {
"file_list": [
("qwen/Qwen2-1.5B-Instruct", "config.json", "models/QwenPrompt/qwen2-1.5b-instruct"),
("qwen/Qwen2-1.5B-Instruct", "generation_config.json", "models/QwenPrompt/qwen2-1.5b-instruct"),
("qwen/Qwen2-1.5B-Instruct", "model.safetensors", "models/QwenPrompt/qwen2-1.5b-instruct"),
("qwen/Qwen2-1.5B-Instruct", "special_tokens_map.json", "models/QwenPrompt/qwen2-1.5b-instruct"),
("qwen/Qwen2-1.5B-Instruct", "tokenizer.json", "models/QwenPrompt/qwen2-1.5b-instruct"),
("qwen/Qwen2-1.5B-Instruct", "tokenizer_config.json", "models/QwenPrompt/qwen2-1.5b-instruct"),
("qwen/Qwen2-1.5B-Instruct", "merges.txt", "models/QwenPrompt/qwen2-1.5b-instruct"),
("qwen/Qwen2-1.5B-Instruct", "vocab.json", "models/QwenPrompt/qwen2-1.5b-instruct"),
],
"load_path": [
"models/QwenPrompt/qwen2-1.5b-instruct",
],
},
# Beautiful Prompt
"BeautifulPrompt": [
("AI-ModelScope/pai-bloom-1b1-text2prompt-sd", "config.json", "models/BeautifulPrompt/pai-bloom-1b1-text2prompt-sd"),
("AI-ModelScope/pai-bloom-1b1-text2prompt-sd", "generation_config.json", "models/BeautifulPrompt/pai-bloom-1b1-text2prompt-sd"),
("AI-ModelScope/pai-bloom-1b1-text2prompt-sd", "model.safetensors", "models/BeautifulPrompt/pai-bloom-1b1-text2prompt-sd"),
("AI-ModelScope/pai-bloom-1b1-text2prompt-sd", "special_tokens_map.json", "models/BeautifulPrompt/pai-bloom-1b1-text2prompt-sd"),
("AI-ModelScope/pai-bloom-1b1-text2prompt-sd", "tokenizer.json", "models/BeautifulPrompt/pai-bloom-1b1-text2prompt-sd"),
("AI-ModelScope/pai-bloom-1b1-text2prompt-sd", "tokenizer_config.json", "models/BeautifulPrompt/pai-bloom-1b1-text2prompt-sd"),
],
"BeautifulPrompt": {
"file_list": [
("AI-ModelScope/pai-bloom-1b1-text2prompt-sd", "config.json", "models/BeautifulPrompt/pai-bloom-1b1-text2prompt-sd"),
("AI-ModelScope/pai-bloom-1b1-text2prompt-sd", "generation_config.json", "models/BeautifulPrompt/pai-bloom-1b1-text2prompt-sd"),
("AI-ModelScope/pai-bloom-1b1-text2prompt-sd", "model.safetensors", "models/BeautifulPrompt/pai-bloom-1b1-text2prompt-sd"),
("AI-ModelScope/pai-bloom-1b1-text2prompt-sd", "special_tokens_map.json", "models/BeautifulPrompt/pai-bloom-1b1-text2prompt-sd"),
("AI-ModelScope/pai-bloom-1b1-text2prompt-sd", "tokenizer.json", "models/BeautifulPrompt/pai-bloom-1b1-text2prompt-sd"),
("AI-ModelScope/pai-bloom-1b1-text2prompt-sd", "tokenizer_config.json", "models/BeautifulPrompt/pai-bloom-1b1-text2prompt-sd"),
],
"load_path": [
"models/BeautifulPrompt/pai-bloom-1b1-text2prompt-sd",
],
},
# Omost prompt
"OmostPrompt":[
("Omost/omost-llama-3-8b-4bits", "model-00001-of-00002.safetensors", "models/OmostPrompt/omost-llama-3-8b-4bits"),
("Omost/omost-llama-3-8b-4bits", "model-00002-of-00002.safetensors", "models/OmostPrompt/omost-llama-3-8b-4bits"),
("Omost/omost-llama-3-8b-4bits", "tokenizer.json", "models/OmostPrompt/omost-llama-3-8b-4bits"),
("Omost/omost-llama-3-8b-4bits", "tokenizer_config.json", "models/OmostPrompt/omost-llama-3-8b-4bits"),
("Omost/omost-llama-3-8b-4bits", "config.json", "models/OmostPrompt/omost-llama-3-8b-4bits"),
("Omost/omost-llama-3-8b-4bits", "generation_config.json", "models/OmostPrompt/omost-llama-3-8b-4bits"),
("Omost/omost-llama-3-8b-4bits", "model.safetensors.index.json", "models/OmostPrompt/omost-llama-3-8b-4bits"),
("Omost/omost-llama-3-8b-4bits", "special_tokens_map.json", "models/OmostPrompt/omost-llama-3-8b-4bits"),
],
"OmostPrompt": {
"file_list": [
("Omost/omost-llama-3-8b-4bits", "model-00001-of-00002.safetensors", "models/OmostPrompt/omost-llama-3-8b-4bits"),
("Omost/omost-llama-3-8b-4bits", "model-00002-of-00002.safetensors", "models/OmostPrompt/omost-llama-3-8b-4bits"),
("Omost/omost-llama-3-8b-4bits", "tokenizer.json", "models/OmostPrompt/omost-llama-3-8b-4bits"),
("Omost/omost-llama-3-8b-4bits", "tokenizer_config.json", "models/OmostPrompt/omost-llama-3-8b-4bits"),
("Omost/omost-llama-3-8b-4bits", "config.json", "models/OmostPrompt/omost-llama-3-8b-4bits"),
("Omost/omost-llama-3-8b-4bits", "generation_config.json", "models/OmostPrompt/omost-llama-3-8b-4bits"),
("Omost/omost-llama-3-8b-4bits", "model.safetensors.index.json", "models/OmostPrompt/omost-llama-3-8b-4bits"),
("Omost/omost-llama-3-8b-4bits", "special_tokens_map.json", "models/OmostPrompt/omost-llama-3-8b-4bits"),
],
"load_path": [
"models/OmostPrompt/omost-llama-3-8b-4bits",
],
},
# Translator
"opus-mt-zh-en": [
("moxying/opus-mt-zh-en", "config.json", "models/translator/opus-mt-zh-en"),
("moxying/opus-mt-zh-en", "generation_config.json", "models/translator/opus-mt-zh-en"),
("moxying/opus-mt-zh-en", "metadata.json", "models/translator/opus-mt-zh-en"),
("moxying/opus-mt-zh-en", "pytorch_model.bin", "models/translator/opus-mt-zh-en"),
("moxying/opus-mt-zh-en", "source.spm", "models/translator/opus-mt-zh-en"),
("moxying/opus-mt-zh-en", "target.spm", "models/translator/opus-mt-zh-en"),
("moxying/opus-mt-zh-en", "tokenizer_config.json", "models/translator/opus-mt-zh-en"),
("moxying/opus-mt-zh-en", "vocab.json", "models/translator/opus-mt-zh-en"),
],
"opus-mt-zh-en": {
"file_list": [
("moxying/opus-mt-zh-en", "config.json", "models/translator/opus-mt-zh-en"),
("moxying/opus-mt-zh-en", "generation_config.json", "models/translator/opus-mt-zh-en"),
("moxying/opus-mt-zh-en", "metadata.json", "models/translator/opus-mt-zh-en"),
("moxying/opus-mt-zh-en", "pytorch_model.bin", "models/translator/opus-mt-zh-en"),
("moxying/opus-mt-zh-en", "source.spm", "models/translator/opus-mt-zh-en"),
("moxying/opus-mt-zh-en", "target.spm", "models/translator/opus-mt-zh-en"),
("moxying/opus-mt-zh-en", "tokenizer_config.json", "models/translator/opus-mt-zh-en"),
("moxying/opus-mt-zh-en", "vocab.json", "models/translator/opus-mt-zh-en"),
],
"load_path": [
"models/translator/opus-mt-zh-en",
],
},
# IP-Adapter
"IP-Adapter-SD": [
("AI-ModelScope/IP-Adapter", "models/image_encoder/model.safetensors", "models/IpAdapter/stable_diffusion/image_encoder"),
@@ -404,32 +424,64 @@ preset_models_on_modelscope = {
("AI-ModelScope/IP-Adapter", "sdxl_models/ip-adapter_sdxl.bin", "models/IpAdapter/stable_diffusion_xl"),
],
# Kolors
"Kolors": [
("Kwai-Kolors/Kolors", "text_encoder/config.json", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "text_encoder/pytorch_model.bin.index.json", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "text_encoder/pytorch_model-00001-of-00007.bin", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "text_encoder/pytorch_model-00002-of-00007.bin", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "text_encoder/pytorch_model-00003-of-00007.bin", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "text_encoder/pytorch_model-00004-of-00007.bin", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "text_encoder/pytorch_model-00005-of-00007.bin", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "text_encoder/pytorch_model-00006-of-00007.bin", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "text_encoder/pytorch_model-00007-of-00007.bin", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "unet/diffusion_pytorch_model.safetensors", "models/kolors/Kolors/unet"),
("Kwai-Kolors/Kolors", "vae/diffusion_pytorch_model.safetensors", "models/kolors/Kolors/vae"),
],
"Kolors": {
"file_list": [
("Kwai-Kolors/Kolors", "text_encoder/config.json", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "text_encoder/pytorch_model.bin.index.json", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "text_encoder/pytorch_model-00001-of-00007.bin", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "text_encoder/pytorch_model-00002-of-00007.bin", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "text_encoder/pytorch_model-00003-of-00007.bin", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "text_encoder/pytorch_model-00004-of-00007.bin", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "text_encoder/pytorch_model-00005-of-00007.bin", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "text_encoder/pytorch_model-00006-of-00007.bin", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "text_encoder/pytorch_model-00007-of-00007.bin", "models/kolors/Kolors/text_encoder"),
("Kwai-Kolors/Kolors", "unet/diffusion_pytorch_model.safetensors", "models/kolors/Kolors/unet"),
("Kwai-Kolors/Kolors", "vae/diffusion_pytorch_model.safetensors", "models/kolors/Kolors/vae"),
],
"load_path": [
"models/kolors/Kolors/text_encoder",
"models/kolors/Kolors/unet/diffusion_pytorch_model.safetensors",
"models/kolors/Kolors/vae/diffusion_pytorch_model.safetensors",
],
},
"SDXL-vae-fp16-fix": [
("AI-ModelScope/sdxl-vae-fp16-fix", "diffusion_pytorch_model.safetensors", "models/sdxl-vae-fp16-fix")
],
# FLUX
"FLUX.1-dev": [
("AI-ModelScope/FLUX.1-dev", "text_encoder/model.safetensors", "models/FLUX/FLUX.1-dev/text_encoder"),
("AI-ModelScope/FLUX.1-dev", "text_encoder_2/config.json", "models/FLUX/FLUX.1-dev/text_encoder_2"),
("AI-ModelScope/FLUX.1-dev", "text_encoder_2/model-00001-of-00002.safetensors", "models/FLUX/FLUX.1-dev/text_encoder_2"),
("AI-ModelScope/FLUX.1-dev", "text_encoder_2/model-00002-of-00002.safetensors", "models/FLUX/FLUX.1-dev/text_encoder_2"),
("AI-ModelScope/FLUX.1-dev", "text_encoder_2/model.safetensors.index.json", "models/FLUX/FLUX.1-dev/text_encoder_2"),
("AI-ModelScope/FLUX.1-dev", "ae.safetensors", "models/FLUX/FLUX.1-dev"),
("AI-ModelScope/FLUX.1-dev", "flux1-dev.safetensors", "models/FLUX/FLUX.1-dev"),
],
"FLUX.1-dev": {
"file_list": [
("AI-ModelScope/FLUX.1-dev", "text_encoder/model.safetensors", "models/FLUX/FLUX.1-dev/text_encoder"),
("AI-ModelScope/FLUX.1-dev", "text_encoder_2/config.json", "models/FLUX/FLUX.1-dev/text_encoder_2"),
("AI-ModelScope/FLUX.1-dev", "text_encoder_2/model-00001-of-00002.safetensors", "models/FLUX/FLUX.1-dev/text_encoder_2"),
("AI-ModelScope/FLUX.1-dev", "text_encoder_2/model-00002-of-00002.safetensors", "models/FLUX/FLUX.1-dev/text_encoder_2"),
("AI-ModelScope/FLUX.1-dev", "text_encoder_2/model.safetensors.index.json", "models/FLUX/FLUX.1-dev/text_encoder_2"),
("AI-ModelScope/FLUX.1-dev", "ae.safetensors", "models/FLUX/FLUX.1-dev"),
("AI-ModelScope/FLUX.1-dev", "flux1-dev.safetensors", "models/FLUX/FLUX.1-dev"),
],
"load_path": [
"models/FLUX/FLUX.1-dev/text_encoder/model.safetensors",
"models/FLUX/FLUX.1-dev/text_encoder_2",
"models/FLUX/FLUX.1-dev/ae.safetensors",
"models/FLUX/FLUX.1-dev/flux1-dev.safetensors"
],
},
"FLUX.1-schnell": {
"file_list": [
("AI-ModelScope/FLUX.1-dev", "text_encoder/model.safetensors", "models/FLUX/FLUX.1-dev/text_encoder"),
("AI-ModelScope/FLUX.1-dev", "text_encoder_2/config.json", "models/FLUX/FLUX.1-dev/text_encoder_2"),
("AI-ModelScope/FLUX.1-dev", "text_encoder_2/model-00001-of-00002.safetensors", "models/FLUX/FLUX.1-dev/text_encoder_2"),
("AI-ModelScope/FLUX.1-dev", "text_encoder_2/model-00002-of-00002.safetensors", "models/FLUX/FLUX.1-dev/text_encoder_2"),
("AI-ModelScope/FLUX.1-dev", "text_encoder_2/model.safetensors.index.json", "models/FLUX/FLUX.1-dev/text_encoder_2"),
("AI-ModelScope/FLUX.1-dev", "ae.safetensors", "models/FLUX/FLUX.1-dev"),
("AI-ModelScope/FLUX.1-schnell", "flux1-schnell.safetensors", "models/FLUX/FLUX.1-schnell"),
],
"load_path": [
"models/FLUX/FLUX.1-dev/text_encoder/model.safetensors",
"models/FLUX/FLUX.1-dev/text_encoder_2",
"models/FLUX/FLUX.1-dev/ae.safetensors",
"models/FLUX/FLUX.1-schnell/flux1-schnell.safetensors"
],
},
# ESRGAN
"ESRGAN_x4": [
("AI-ModelScope/Real-ESRGAN", "RealESRGAN_x4.pth", "models/ESRGAN"),
@@ -439,17 +491,24 @@ preset_models_on_modelscope = {
("AI-ModelScope/RIFE", "flownet.pkl", "models/RIFE"),
],
# CogVideo
"CogVideoX-5B": [
("ZhipuAI/CogVideoX-5b", "text_encoder/config.json", "models/CogVideo/CogVideoX-5b/text_encoder"),
("ZhipuAI/CogVideoX-5b", "text_encoder/model.safetensors.index.json", "models/CogVideo/CogVideoX-5b/text_encoder"),
("ZhipuAI/CogVideoX-5b", "text_encoder/model-00001-of-00002.safetensors", "models/CogVideo/CogVideoX-5b/text_encoder"),
("ZhipuAI/CogVideoX-5b", "text_encoder/model-00002-of-00002.safetensors", "models/CogVideo/CogVideoX-5b/text_encoder"),
("ZhipuAI/CogVideoX-5b", "transformer/config.json", "models/CogVideo/CogVideoX-5b/transformer"),
("ZhipuAI/CogVideoX-5b", "transformer/diffusion_pytorch_model.safetensors.index.json", "models/CogVideo/CogVideoX-5b/transformer"),
("ZhipuAI/CogVideoX-5b", "transformer/diffusion_pytorch_model-00001-of-00002.safetensors", "models/CogVideo/CogVideoX-5b/transformer"),
("ZhipuAI/CogVideoX-5b", "transformer/diffusion_pytorch_model-00002-of-00002.safetensors", "models/CogVideo/CogVideoX-5b/transformer"),
("ZhipuAI/CogVideoX-5b", "vae/diffusion_pytorch_model.safetensors", "models/CogVideo/CogVideoX-5b/vae"),
],
"CogVideoX-5B": {
"file_list": [
("ZhipuAI/CogVideoX-5b", "text_encoder/config.json", "models/CogVideo/CogVideoX-5b/text_encoder"),
("ZhipuAI/CogVideoX-5b", "text_encoder/model.safetensors.index.json", "models/CogVideo/CogVideoX-5b/text_encoder"),
("ZhipuAI/CogVideoX-5b", "text_encoder/model-00001-of-00002.safetensors", "models/CogVideo/CogVideoX-5b/text_encoder"),
("ZhipuAI/CogVideoX-5b", "text_encoder/model-00002-of-00002.safetensors", "models/CogVideo/CogVideoX-5b/text_encoder"),
("ZhipuAI/CogVideoX-5b", "transformer/config.json", "models/CogVideo/CogVideoX-5b/transformer"),
("ZhipuAI/CogVideoX-5b", "transformer/diffusion_pytorch_model.safetensors.index.json", "models/CogVideo/CogVideoX-5b/transformer"),
("ZhipuAI/CogVideoX-5b", "transformer/diffusion_pytorch_model-00001-of-00002.safetensors", "models/CogVideo/CogVideoX-5b/transformer"),
("ZhipuAI/CogVideoX-5b", "transformer/diffusion_pytorch_model-00002-of-00002.safetensors", "models/CogVideo/CogVideoX-5b/transformer"),
("ZhipuAI/CogVideoX-5b", "vae/diffusion_pytorch_model.safetensors", "models/CogVideo/CogVideoX-5b/vae"),
],
"load_path": [
"models/CogVideo/CogVideoX-5b/text_encoder",
"models/CogVideo/CogVideoX-5b/transformer",
"models/CogVideo/CogVideoX-5b/vae/diffusion_pytorch_model.safetensors",
],
},
}
Preset_model_id: TypeAlias = Literal[
"HunyuanDiT",
@@ -481,6 +540,7 @@ Preset_model_id: TypeAlias = Literal[
"SDXL-vae-fp16-fix",
"ControlNet_union_sdxl_promax",
"FLUX.1-dev",
"FLUX.1-schnell",
"SDXL_lora_zyd232_ChineseInkStyle_SDXL_v1_0",
"QwenPrompt",
"OmostPrompt",

69
diffsynth/models/downloader.py
View File

@@ -8,28 +8,27 @@ from ..configs.model_config import preset_models_on_huggingface, preset_models_o
def download_from_modelscope(model_id, origin_file_path, local_dir):
os.makedirs(local_dir, exist_ok=True)
if os.path.basename(origin_file_path) in os.listdir(local_dir):
print(f" {os.path.basename(origin_file_path)} has been already in {local_dir}.")
return
file_name = os.path.basename(origin_file_path)
if file_name in os.listdir(local_dir):
print(f" {file_name} has been already in {local_dir}.")
else:
print(f" Start downloading {os.path.join(local_dir, os.path.basename(origin_file_path))}")
snapshot_download(model_id, allow_file_pattern=origin_file_path, local_dir=local_dir)
downloaded_file_path = os.path.join(local_dir, origin_file_path)
target_file_path = os.path.join(local_dir, os.path.split(origin_file_path)[-1])
if downloaded_file_path != target_file_path:
shutil.move(downloaded_file_path, target_file_path)
shutil.rmtree(os.path.join(local_dir, origin_file_path.split("/")[0]))
print(f" Start downloading {os.path.join(local_dir, file_name)}")
snapshot_download(model_id, allow_file_pattern=origin_file_path, local_dir=local_dir)
downloaded_file_path = os.path.join(local_dir, origin_file_path)
target_file_path = os.path.join(local_dir, os.path.split(origin_file_path)[-1])
if downloaded_file_path != target_file_path:
shutil.move(downloaded_file_path, target_file_path)
shutil.rmtree(os.path.join(local_dir, origin_file_path.split("/")[0]))
def download_from_huggingface(model_id, origin_file_path, local_dir):
os.makedirs(local_dir, exist_ok=True)
file_name = os.path.basename(origin_file_path)
if file_name in os.listdir(local_dir):
return f"{file_name} has already been downloaded to {local_dir}."
print(f" {file_name} has been already in {local_dir}.")
else:
print(f"Start downloading {os.path.join(local_dir, file_name)}")
print(f" Start downloading {os.path.join(local_dir, file_name)}")
hf_hub_download(model_id, origin_file_path, local_dir=local_dir)
downloaded_file_path = os.path.join(local_dir, origin_file_path)
target_file_path = os.path.join(local_dir, file_name)
if downloaded_file_path != target_file_path:
@@ -51,16 +50,47 @@ website_to_download_fn = {
}
def download_customized_models(
model_id,
origin_file_path,
local_dir,
downloading_priority: List[Preset_model_website] = ["ModelScope", "HuggingFace"],
):
downloaded_files = []
for website in downloading_priority:
# Check if the file is downloaded.
file_to_download = os.path.join(local_dir, os.path.basename(origin_file_path))
if file_to_download in downloaded_files:
continue
# Download
website_to_download_fn[website](model_id, origin_file_path, local_dir)
if os.path.basename(origin_file_path) in os.listdir(local_dir):
downloaded_files.append(file_to_download)
return downloaded_files
def download_models(
model_id_list: List[Preset_model_id] = [],
downloading_priority: List[Preset_model_website] = ["ModelScope", "HuggingFace"],
):
print(f"Downloading models: {model_id_list}")
downloaded_files = []
load_files = []
for model_id in model_id_list:
for website in downloading_priority:
if model_id in website_to_preset_models[website]:
for model_id, origin_file_path, local_dir in website_to_preset_models[website][model_id]:
# Parse model metadata
model_metadata = website_to_preset_models[website][model_id]
if isinstance(model_metadata, list):
file_data = model_metadata
else:
file_data = model_metadata.get("file_list", [])
# Try downloading the model from this website.
model_files = []
for model_id, origin_file_path, local_dir in file_data:
# Check if the file is downloaded.
file_to_download = os.path.join(local_dir, os.path.basename(origin_file_path))
if file_to_download in downloaded_files:
@@ -69,4 +99,13 @@ def download_models(
website_to_download_fn[website](model_id, origin_file_path, local_dir)
if os.path.basename(origin_file_path) in os.listdir(local_dir):
downloaded_files.append(file_to_download)
return downloaded_files
model_files.append(file_to_download)
# If the model is successfully downloaded, break.
if len(model_files) > 0:
if isinstance(model_metadata, dict) and "load_path" in model_metadata:
model_files = model_metadata["load_path"]
load_files.extend(model_files)
break
return load_files

2
diffsynth/models/model_manager.py
View File

@@ -4,7 +4,7 @@ from torch import Tensor
from typing_extensions import Literal, TypeAlias
from typing import List
from .downloader import download_models, Preset_model_id, Preset_model_website
from .downloader import download_models, download_customized_models, Preset_model_id, Preset_model_website
from .sd_text_encoder import SDTextEncoder
from .sd_unet import SDUNet

6
diffsynth/pipelines/flux_image.py
View File

@@ -65,7 +65,7 @@ class FluxImagePipeline(BasePipeline):
return {"prompt_emb": prompt_emb, "pooled_prompt_emb": pooled_prompt_emb, "text_ids": text_ids}
def prepare_extra_input(self, latents=None, guidance=0.0):
def prepare_extra_input(self, latents=None, guidance=1.0):
latent_image_ids = self.dit.prepare_image_ids(latents)
guidance = torch.Tensor([guidance] * latents.shape[0]).to(device=latents.device, dtype=latents.dtype)
return {"image_ids": latent_image_ids, "guidance": guidance}
@@ -80,13 +80,13 @@ class FluxImagePipeline(BasePipeline):
mask_scales= None,
negative_prompt="",
cfg_scale=1.0,
embedded_guidance=0.0,
embedded_guidance=1.0,
input_image=None,
denoising_strength=1.0,
height=1024,
width=1024,
num_inference_steps=30,
t5_sequence_length=256,
t5_sequence_length=512,
tiled=False,
tile_size=128,
tile_stride=64,