fixed recammaster
@ -23,7 +23,7 @@ WanGP supports the Wan (and derived models), Hunyuan Video and LTV Video models
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### August 8 2025: WanGP v7.74 - Qwen Rebirth part 2
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					### August 8 2025: WanGP v7.74 - Qwen Rebirth part 2
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Added support for Qwen Lightning lora for a 8 steps generation (https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-8steps-V1.0.safetensors). Lora is not normalized and you can use a multiplier around 0.1.
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					Added support for Qwen Lightning lora for a 8 steps generation (https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-8steps-V1.0.safetensors). Lora is not normalized and you can use a multiplier around 0.1.
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Mag Cache support for all the Wan2.2 models
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					Mag Cache support for all the Wan2.2 models Don't forget to set guidance to 1 and 8 denoising steps , your gen will be 7x faster !
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### August 8 2025: WanGP v7.73 - Qwen Rebirth
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					### August 8 2025: WanGP v7.73 - Qwen Rebirth
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Ever wondered what impact not using Guidance has on a model that expects it ? Just look at Qween Image in WanGP 7.71 whose outputs were erratic. Somehow I had convinced myself that Qwen was a distilled model. In fact Qwen was dying for a negative prompt. And in WanGP 7.72 there is at last one for him.
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					Ever wondered what impact not using Guidance has on a model that expects it ? Just look at Qween Image in WanGP 7.71 whose outputs were erratic. Somehow I had convinced myself that Qwen was a distilled model. In fact Qwen was dying for a negative prompt. And in WanGP 7.72 there is at last one for him.
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@ -40,7 +40,7 @@ def get_relative_pose(cam_params):
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def get_camera_embedding(cam_type, num_frames=81):
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					def get_camera_embedding(cam_type, num_frames=81):
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    # load camera
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					    # load camera
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    tgt_camera_path = "wan/camera_extrinsics.json"
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					    tgt_camera_path = "models/wan/camera_extrinsics.json"
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    with open(tgt_camera_path, 'r') as file:
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					    with open(tgt_camera_path, 'r') as file:
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        cam_data = json.load(file)
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					        cam_data = json.load(file)
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