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sat/configs/cogvideox1.5_5b.yaml

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@@ -23,7 +23,7 @@ model:
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params:
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time_embed_dim: 512
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elementwise_affine: True
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num_frames: 81
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num_frames: 81 # for 5 seconds and 161 for 10 seconds
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time_compressed_rate: 4
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latent_width: 300
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latent_height: 300

sat/configs/cogvideox1.5_5b_i2v.yaml

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@@ -25,11 +25,10 @@ model:
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network_config:
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target: dit_video_concat.DiffusionTransformer
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params:
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# space_interpolation: 1.875
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ofs_embed_dim: 512
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time_embed_dim: 512
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elementwise_affine: True
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num_frames: 81
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num_frames: 81 # for 5 seconds and 161 for 10 seconds
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time_compressed_rate: 4
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latent_width: 300
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latent_height: 300

sat/configs/inference.yaml

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args:
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image2video: False # True for image2video, False for text2video
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# image2video: True # True for image2video, False for text2video
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latent_channels: 16
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mode: inference
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load: "{your CogVideoX SAT folder}/transformer" # This is for Full model without lora adapter
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# load: "{your lora folder} such as zRzRzRzRzRzRzR/lora-disney-08-20-13-28" # This is for Full model without lora adapter
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batch_size: 1
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input_type: txt
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input_file: configs/test.txt
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sampling_image_size: [480, 720]
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sampling_num_frames: 13 # Must be 13, 11 or 9
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sampling_fps: 8
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# fp16: True # For CogVideoX-2B
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bf16: True # For CogVideoX-5B and CoGVideoX-5B-I2V
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output_dir: outputs/
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sampling_image_size: [768, 1360] # remove this for I2V
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sampling_num_frames: 22 # 42 for 10 seconds and 22 for 5 seconds
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sampling_fps: 16
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bf16: True
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output_dir: outputs
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force_inference: True

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