Tribal Girl with Animatrix
Input
prompt
Specify things to see in the output
<lora:ringo:0.65>, (best quality), big head, face surprised, (ringo with huge breasts:1.2), in a tribal outfit in a tribes camp, portrait <lora:add_detail:1> <lora:LowRA:0.2>
negative_prompt
Specify things to not see in the output
(worst quality, bad quality, child, cropped:1.4), nipples, nsfw, more than 1 person
num_outputs
Number of output images
4
width
Output image width
768
height
Output image height
768
enhance_face_with_adetailer
Enhance face with adetailer
true
enhance_hands_with_adetailer
Enhance hands with adetailer
true
adetailer_denoising_strength
1: completely redraw face or hands / 0: no effect on output images
0.55
detail
Enhance/diminish detail while keeping the overall style/character
0
brightness
Adjust brightness
0
contrast
Adjust contrast
0
saturation
Adjust saturation
0
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
4014846642
input_image
Base image that the output should be generated from. This is useful when you want to add some detail to input_image. For example, if prompt is "sunglasses" and input_image has a man, there is the man wearing sunglasses in the output.
input_image_redrawing_strength
How differ the output is from input_image. Used only when input_image is given.
0.55
reference_image
Image with which the output should share identity (e.g. face of a person or type of a dog)
reference_image_strength
Strength of applying reference_image. Used only when reference_image is given.
1
reference_pose_image
Image with a reference pose
reference_pose_strength
Strength of applying reference_pose_image. Used only when reference_pose_image is given.
1
reference_depth_image
Image with a reference depth
reference_depth_strength
Strength of applying reference_depth_image. Used only when reference_depth_image is given.
1
sampler
Sampler type
DPM++ 2M Karras
samping_steps
Number of denoising steps
38
cfg_scale
Scale for classifier-free guidance
10
clip_skip
The number of last layers of CLIP network to skip
2
vae
Select VAE
blessed2_fp16.safetensors
lora_1
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
lora_2
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
lora_3
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
embedding_1
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
embedding_2
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
embedding_3
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
disable_prompt_modification
Disable automatically adding suggested prompt modification. Built-in LoRAs and trigger words will remain.
false
Output
Finished in 109.4 seconds
Setting up the model...
Processing...
Loading VAE weight: models/VAE/blessed2_fp16.safetensors
Full prompt: <lora:ringo:0.65>, (best quality), big head, face surprised, (ringo with huge breasts:1.2), in a tribal outfit in a tribes camp, portrait <lora:LowRA:0.2>
Full negative prompt: (worst quality, bad quality, child, cropped:1.4), nipples, nsfw, more than 1 person
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Decoding latents in cuda:0...
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0: 640x640 1 face, 7.8ms
Speed: 3.3ms preprocess, 7.8ms inference, 31.5ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
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0: 640x640 2 hands, 7.2ms
Speed: 2.9ms preprocess, 7.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
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A tensor with all NaNs was produced in VAE.
Converted VAE into 32-bit float and retry.
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0: 640x640 1 face, 7.4ms
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0: 640x640 2 hands, 7.2ms
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Decoding latents in cuda:0...
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0: 640x640 1 face, 7.4ms
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Decoding latents in cuda:0...
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0: 640x640 2 hands, 7.1ms
Speed: 2.8ms preprocess, 7.1ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
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Move latents to cpu...
done in 0.0s
Finished.
prompt
Specify things to see in the output
<lora:ringo:0.65>, (best quality), big head, face surprised, (ringo with huge breasts:1.2), in a tribal outfit in a tribes camp, portrait <lora:add_detail:1> <lora:LowRA:0.2>
negative_prompt
Specify things to not see in the output
(worst quality, bad quality, child, cropped:1.4), nipples, nsfw, more than 1 person
num_outputs
Number of output images
4
width
Output image width
768
height
Output image height
768
enhance_face_with_adetailer
Enhance face with adetailer
true
enhance_hands_with_adetailer
Enhance hands with adetailer
true
adetailer_denoising_strength
1: completely redraw face or hands / 0: no effect on output images
0.55
detail
Enhance/diminish detail while keeping the overall style/character
0
brightness
Adjust brightness
0
contrast
Adjust contrast
0
saturation
Adjust saturation
0
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
4014846642
input_image
Base image that the output should be generated from. This is useful when you want to add some detail to input_image. For example, if prompt is "sunglasses" and input_image has a man, there is the man wearing sunglasses in the output.
input_image_redrawing_strength
How differ the output is from input_image. Used only when input_image is given.
0.55
reference_image
Image with which the output should share identity (e.g. face of a person or type of a dog)
reference_image_strength
Strength of applying reference_image. Used only when reference_image is given.
1
reference_pose_image
Image with a reference pose
reference_pose_strength
Strength of applying reference_pose_image. Used only when reference_pose_image is given.
1
reference_depth_image
Image with a reference depth
reference_depth_strength
Strength of applying reference_depth_image. Used only when reference_depth_image is given.
1
sampler
Sampler type
DPM++ 2M Karras
samping_steps
Number of denoising steps
38
cfg_scale
Scale for classifier-free guidance
10
clip_skip
The number of last layers of CLIP network to skip
2
vae
Select VAE
blessed2_fp16.safetensors
lora_1
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
lora_2
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
lora_3
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
embedding_1
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
embedding_2
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
embedding_3
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
disable_prompt_modification
Disable automatically adding suggested prompt modification. Built-in LoRAs and trigger words will remain.
false
Finished in 109.4 seconds
Setting up the model...
Processing...
Loading VAE weight: models/VAE/blessed2_fp16.safetensors
Full prompt: <lora:ringo:0.65>, (best quality), big head, face surprised, (ringo with huge breasts:1.2), in a tribal outfit in a tribes camp, portrait <lora:LowRA:0.2>
Full negative prompt: (worst quality, bad quality, child, cropped:1.4), nipples, nsfw, more than 1 person
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Decoding latents in cuda:0...
done in 1.0s
Move latents to cpu...
done in 0.02s
0: 640x640 1 face, 7.8ms
Speed: 3.3ms preprocess, 7.8ms inference, 31.5ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
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Move latents to cpu...
done in 0.0s
0: 640x640 2 hands, 7.2ms
Speed: 2.9ms preprocess, 7.2ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
===========================================
A tensor with all NaNs was produced in VAE.
Converted VAE into 32-bit float and retry.
===========================================
done in 0.44s
Move latents to cpu...
done in 0.23s
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Decoding latents in cuda:0...
done in 0.42s
Move latents to cpu...
done in 0.0s
0: 640x640 2 faces, 7.5ms
Speed: 3.0ms preprocess, 7.5ms inference, 1.8ms postprocess per image at shape (1, 3, 640, 640)
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81%|████████ | 17/21 [00:02<00:00, 6.29it/s]
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Decoding latents in cuda:0...
done in 0.41s
Move latents to cpu...
done in 0.0s
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81%|████████ | 17/21 [00:02<00:00, 6.17it/s]
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100%|██████████| 21/21 [00:03<00:00, 6.27it/s]
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Decoding latents in cuda:0...
done in 0.42s
Move latents to cpu...
done in 0.0s
0: 640x640 3 hands, 7.2ms
Speed: 2.9ms preprocess, 7.2ms inference, 1.9ms postprocess per image at shape (1, 3, 640, 640)
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38%|███▊ | 8/21 [00:01<00:02, 6.21it/s]
43%|████▎ | 9/21 [00:01<00:01, 6.15it/s]
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81%|████████ | 17/21 [00:02<00:00, 5.76it/s]
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100%|██████████| 21/21 [00:03<00:00, 6.12it/s]
100%|██████████| 21/21 [00:03<00:00, 6.16it/s]
Decoding latents in cuda:0...
done in 0.42s
Move latents to cpu...
done in 0.0s
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57%|█████▋ | 12/21 [00:01<00:01, 6.29it/s]
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67%|██████▋ | 14/21 [00:02<00:01, 6.30it/s]
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76%|███████▌ | 16/21 [00:02<00:00, 6.37it/s]
81%|████████ | 17/21 [00:02<00:00, 6.31it/s]
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100%|██████████| 21/21 [00:03<00:00, 6.31it/s]
100%|██████████| 21/21 [00:03<00:00, 6.31it/s]
Decoding latents in cuda:0...
done in 0.41s
Move latents to cpu...
done in 0.0s
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43%|████▎ | 9/21 [00:01<00:01, 6.31it/s]
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57%|█████▋ | 12/21 [00:01<00:01, 6.28it/s]
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67%|██████▋ | 14/21 [00:02<00:01, 6.30it/s]
71%|███████▏ | 15/21 [00:02<00:00, 6.33it/s]
76%|███████▌ | 16/21 [00:02<00:00, 6.33it/s]
81%|████████ | 17/21 [00:02<00:00, 6.28it/s]
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100%|██████████| 21/21 [00:03<00:00, 6.27it/s]
100%|██████████| 21/21 [00:03<00:00, 6.29it/s]
Decoding latents in cuda:0...
done in 0.41s
Move latents to cpu...
done in 0.0s
0: 640x640 1 face, 7.4ms
Speed: 2.9ms preprocess, 7.4ms inference, 1.9ms postprocess per image at shape (1, 3, 640, 640)
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67%|██████▋ | 14/21 [00:02<00:01, 6.22it/s]
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76%|███████▌ | 16/21 [00:02<00:00, 6.31it/s]
81%|████████ | 17/21 [00:02<00:00, 6.36it/s]
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100%|██████████| 21/21 [00:03<00:00, 6.20it/s]
100%|██████████| 21/21 [00:03<00:00, 6.34it/s]
Decoding latents in cuda:0...
done in 0.41s
Move latents to cpu...
done in 0.0s
0: 640x640 2 hands, 7.2ms
Speed: 3.0ms preprocess, 7.2ms inference, 1.6ms postprocess per image at shape (1, 3, 640, 640)
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43%|████▎ | 9/21 [00:01<00:01, 6.32it/s]
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76%|███████▌ | 16/21 [00:02<00:00, 6.31it/s]
81%|████████ | 17/21 [00:02<00:00, 6.36it/s]
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100%|██████████| 21/21 [00:03<00:00, 6.26it/s]
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Decoding latents in cuda:0...
done in 0.41s
Move latents to cpu...
done in 0.0s
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57%|█████▋ | 12/21 [00:01<00:01, 6.30it/s]
62%|██████▏ | 13/21 [00:02<00:01, 6.30it/s]
67%|██████▋ | 14/21 [00:02<00:01, 6.32it/s]
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76%|███████▌ | 16/21 [00:02<00:00, 6.38it/s]
81%|████████ | 17/21 [00:02<00:00, 6.34it/s]
86%|████████▌ | 18/21 [00:02<00:00, 6.27it/s]
90%|█████████ | 19/21 [00:03<00:00, 6.26it/s]
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100%|██████████| 21/21 [00:03<00:00, 6.29it/s]
100%|██████████| 21/21 [00:03<00:00, 6.33it/s]
Decoding latents in cuda:0...
done in 0.41s
Move latents to cpu...
done in 0.0s
0: 640x640 1 face, 7.4ms
Speed: 2.7ms preprocess, 7.4ms inference, 1.8ms postprocess per image at shape (1, 3, 640, 640)
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67%|██████▋ | 14/21 [00:02<00:01, 6.33it/s]
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76%|███████▌ | 16/21 [00:02<00:00, 6.38it/s]
81%|████████ | 17/21 [00:02<00:00, 6.43it/s]
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100%|██████████| 21/21 [00:03<00:00, 6.35it/s]
100%|██████████| 21/21 [00:03<00:00, 6.41it/s]
Decoding latents in cuda:0...
done in 0.41s
Move latents to cpu...
done in 0.0s
0: 640x640 2 hands, 7.1ms
Speed: 2.8ms preprocess, 7.1ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 640)
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81%|████████ | 17/21 [00:02<00:00, 6.29it/s]
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100%|██████████| 21/21 [00:03<00:00, 6.27it/s]
100%|██████████| 21/21 [00:03<00:00, 6.38it/s]
Decoding latents in cuda:0...
done in 0.41s
Move latents to cpu...
done in 0.0s
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100%|██████████| 21/21 [00:03<00:00, 6.37it/s]
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Decoding latents in cuda:0...
done in 0.41s
Move latents to cpu...
done in 0.0s
Finished.