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fix: correct LoRA loading and resolution dimensions

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- Fix LoRA loading by specifying 'transformer' component
- Swap width/height order in RESOLUTION_MAP to match actual usage
This commit is contained in:
OleehyO 2025-01-13 10:49:46 +00:00
parent 86a0226f80
commit 4f1cc66815
1 changed files with 7 additions and 7 deletions
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14
inference/cli_demo.py
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@ -36,12 +36,12 @@ logging.basicConfig(level=logging.INFO)
# Recommended resolution for each model (width, height)
RESOLUTION_MAP = {
# cogvideox1.5-*
"cogvideox1.5-5b-i2v": (1360, 768),
"cogvideox1.5-5b": (1360, 768),
"cogvideox1.5-5b-i2v": (768, 1360),
"cogvideox1.5-5b": (768, 1360),
# cogvideox-*
"cogvideox-5b-i2v": (720, 480),
"cogvideox-5b": (720, 480),
"cogvideox-2b": (720, 480),
"cogvideox-5b-i2v": (480, 720),
"cogvideox-5b": (480, 720),
"cogvideox-2b": (480, 720),
}
@ -94,7 +94,7 @@ def generate_video(
model_name = model_path.split("/")[-1].lower()
desired_resolution = RESOLUTION_MAP[model_name]
if width is None or height is None:
width, height = desired_resolution
height, width = desired_resolution
logging.info(f"\033[1mUsing default resolution {desired_resolution} for {model_name}\033[0m")
elif (width, height) != desired_resolution:
if generate_type == "i2v":
@ -121,7 +121,7 @@ def generate_video(
# If you're using with lora, add this code
if lora_path:
pipe.load_lora_weights(lora_path, weight_name="pytorch_lora_weights.safetensors", adapter_name="test_1")
pipe.fuse_lora(lora_scale=1 / lora_rank)
pipe.fuse_lora(components=["transformer"], lora_scale=1/lora_rank)
# 2. Set Scheduler.
# Can be changed to `CogVideoXDPMScheduler` or `CogVideoXDDIMScheduler`.