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Riding Dragons with Mjolnir Turbo SDXL
mjolnir-turbo-sdxl:lightning
evevalentine2017
evevalentine2017
·
Mar 3
379
Input
prompt
Specify things to see in the output
(best quality), (masterpiece), (detailed), elf riding a dragon, (fantasy illustration)1.3, enchanting Dragon, elf on the shelf, mystical design, (many gnomes)1.4 (whimsical charm).4 Otherworldly charm, mystical sky, (Luis Royo)1.2, (Yoshitaka Amano)1.1, moonlit night, soft colors, (detailed cloudscape)1.3, (high-resolution)1.2 (gnomes everywhere)1.2
negative_prompt
Specify things to not see in the output
Bad quality, worst quality, watermark
num_outputs
Number of output images
3
width
Output image width
1024
height
Output image height
768
enhance_face_with_adetailer
Enhance face with adetailer
true
enhance_hands_with_adetailer
Enhance hands with adetailer
false
adetailer_denoising_strength
1: completely redraw face or hands / 0: no effect on output images
0.45
detail
Enhance/diminish detail while keeping the overall style/character
0
brightness
Adjust brightness
0
contrast
Adjust contrast
0
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
2090560894
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++ 2S a
samping_steps
Number of denoising steps
10
cfg_scale
Scale for classifier-free guidance
2.5
clip_skip
The number of last layers of CLIP network to skip
2
vae
Select VAE
sdxl_vae.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
https://files.tungsten.run/uploads/1cbbad62f9b4420eb34d42a9d5fc5531/00000-2090560894.webp
https://files.tungsten.run/uploads/27b388fde337424c9083bf01687dc67f/00001-2090560895.webp
https://files.tungsten.run/uploads/76b32ff13c0d41cfa555069eb698e888/00002-2090560896.webp
Finished in 48.8 seconds
Setting up the model... Preparing inputs... Processing... Loading VAE weight: models/VAE/sdxl_vae.safetensors Full prompt: (best quality), (masterpiece), (detailed), elf riding a dragon, (fantasy illustration)1.3, enchanting Dragon, elf on the shelf, mystical design, (many gnomes)1.4 (whimsical charm).4 Otherworldly charm, mystical sky, (Luis Royo)1.2, (Yoshitaka Amano)1.1, moonlit night, soft colors, (detailed cloudscape)1.3, (high-resolution)1.2 (gnomes everywhere)1.2 Full negative prompt: Bad quality, worst quality, watermark 0%| | 0/10 [00:00<?, ?it/s] 10%|█ | 1/10 [00:01<00:16, 1.88s/it] 20%|██ | 2/10 [00:03<00:15, 1.97s/it] 30%|███ | 3/10 [00:05<00:13, 1.91s/it] 40%|████ | 4/10 [00:07<00:11, 1.84s/it] 50%|█████ | 5/10 [00:09<00:08, 1.80s/it] 60%|██████ | 6/10 [00:10<00:07, 1.78s/it] 70%|███████ | 7/10 [00:12<00:05, 1.76s/it] 80%|████████ | 8/10 [00:14<00:03, 1.75s/it] 90%|█████████ | 9/10 [00:16<00:01, 1.74s/it] 100%|██████████| 10/10 [00:16<00:00, 1.47s/it] 100%|██████████| 10/10 [00:16<00:00, 1.70s/it] Decoding latents in cuda:0... done in 1.7s Move latents to cpu... done in 0.02s 0: 480x640 1 face, 158.6ms Speed: 2.6ms preprocess, 158.6ms inference, 28.9ms postprocess per image at shape (1, 3, 480, 640) 0%| | 0/5 [00:00<?, ?it/s] 20%|██ | 1/5 [00:01<00:05, 1.45s/it] 40%|████ | 2/5 [00:02<00:03, 1.30s/it] 60%|██████ | 3/5 [00:03<00:02, 1.25s/it] 80%|████████ | 4/5 [00:05<00:01, 1.24s/it] 100%|██████████| 5/5 [00:05<00:00, 1.01s/it] 100%|██████████| 5/5 [00:05<00:00, 1.13s/it] Decoding latents in cuda:0... done in 0.55s Move latents to cpu... done in 0.0s 0: 480x640 1 face, 8.1ms Speed: 2.4ms preprocess, 8.1ms inference, 1.3ms postprocess per image at shape (1, 3, 480, 640) 0%| | 0/5 [00:00<?, ?it/s] 20%|██ | 1/5 [00:01<00:04, 1.22s/it] 40%|████ | 2/5 [00:02<00:03, 1.22s/it] 60%|██████ | 3/5 [00:03<00:02, 1.23s/it] 80%|████████ | 4/5 [00:04<00:01, 1.25s/it] 100%|██████████| 5/5 [00:05<00:00, 1.04s/it] 100%|██████████| 5/5 [00:05<00:00, 1.12s/it] Decoding latents in cuda:0... done in 0.55s Move latents to cpu... done in 0.0s 0: 480x640 1 face, 7.9ms Speed: 2.4ms preprocess, 7.9ms inference, 1.5ms postprocess per image at shape (1, 3, 480, 640) 0%| | 0/5 [00:00<?, ?it/s] 20%|██ | 1/5 [00:01<00:04, 1.24s/it] 40%|████ | 2/5 [00:02<00:03, 1.23s/it] 60%|██████ | 3/5 [00:03<00:02, 1.23s/it] 80%|████████ | 4/5 [00:04<00:01, 1.25s/it] 100%|██████████| 5/5 [00:05<00:00, 1.02s/it] 100%|██████████| 5/5 [00:05<00:00, 1.12s/it] Decoding latents in cuda:0... done in 0.55s Move latents to cpu... done in 0.0s Uploading outputs... Finished.
prompt
Specify things to see in the output
(best quality), (masterpiece), (detailed), elf riding a dragon, (fantasy illustration)1.3, enchanting Dragon, elf on the shelf, mystical design, (many gnomes)1.4 (whimsical charm).4 Otherworldly charm, mystical sky, (Luis Royo)1.2, (Yoshitaka Amano)1.1, moonlit night, soft colors, (detailed cloudscape)1.3, (high-resolution)1.2 (gnomes everywhere)1.2
negative_prompt
Specify things to not see in the output
Bad quality, worst quality, watermark
num_outputs
Number of output images
3
width
Output image width
1024
height
Output image height
768
enhance_face_with_adetailer
Enhance face with adetailer
true
enhance_hands_with_adetailer
Enhance hands with adetailer
false
adetailer_denoising_strength
1: completely redraw face or hands / 0: no effect on output images
0.45
detail
Enhance/diminish detail while keeping the overall style/character
0
brightness
Adjust brightness
0
contrast
Adjust contrast
0
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
2090560894
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++ 2S a
samping_steps
Number of denoising steps
10
cfg_scale
Scale for classifier-free guidance
2.5
clip_skip
The number of last layers of CLIP network to skip
2
vae
Select VAE
sdxl_vae.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
https://files.tungsten.run/uploads/1cbbad62f9b4420eb34d42a9d5fc5531/00000-2090560894.webp
https://files.tungsten.run/uploads/27b388fde337424c9083bf01687dc67f/00001-2090560895.webp
https://files.tungsten.run/uploads/76b32ff13c0d41cfa555069eb698e888/00002-2090560896.webp
Finished in 48.8 seconds
Setting up the model... Preparing inputs... Processing... Loading VAE weight: models/VAE/sdxl_vae.safetensors Full prompt: (best quality), (masterpiece), (detailed), elf riding a dragon, (fantasy illustration)1.3, enchanting Dragon, elf on the shelf, mystical design, (many gnomes)1.4 (whimsical charm).4 Otherworldly charm, mystical sky, (Luis Royo)1.2, (Yoshitaka Amano)1.1, moonlit night, soft colors, (detailed cloudscape)1.3, (high-resolution)1.2 (gnomes everywhere)1.2 Full negative prompt: Bad quality, worst quality, watermark 0%| | 0/10 [00:00<?, ?it/s] 10%|█ | 1/10 [00:01<00:16, 1.88s/it] 20%|██ | 2/10 [00:03<00:15, 1.97s/it] 30%|███ | 3/10 [00:05<00:13, 1.91s/it] 40%|████ | 4/10 [00:07<00:11, 1.84s/it] 50%|█████ | 5/10 [00:09<00:08, 1.80s/it] 60%|██████ | 6/10 [00:10<00:07, 1.78s/it] 70%|███████ | 7/10 [00:12<00:05, 1.76s/it] 80%|████████ | 8/10 [00:14<00:03, 1.75s/it] 90%|█████████ | 9/10 [00:16<00:01, 1.74s/it] 100%|██████████| 10/10 [00:16<00:00, 1.47s/it] 100%|██████████| 10/10 [00:16<00:00, 1.70s/it] Decoding latents in cuda:0... done in 1.7s Move latents to cpu... done in 0.02s 0: 480x640 1 face, 158.6ms Speed: 2.6ms preprocess, 158.6ms inference, 28.9ms postprocess per image at shape (1, 3, 480, 640) 0%| | 0/5 [00:00<?, ?it/s] 20%|██ | 1/5 [00:01<00:05, 1.45s/it] 40%|████ | 2/5 [00:02<00:03, 1.30s/it] 60%|██████ | 3/5 [00:03<00:02, 1.25s/it] 80%|████████ | 4/5 [00:05<00:01, 1.24s/it] 100%|██████████| 5/5 [00:05<00:00, 1.01s/it] 100%|██████████| 5/5 [00:05<00:00, 1.13s/it] Decoding latents in cuda:0... done in 0.55s Move latents to cpu... done in 0.0s 0: 480x640 1 face, 8.1ms Speed: 2.4ms preprocess, 8.1ms inference, 1.3ms postprocess per image at shape (1, 3, 480, 640) 0%| | 0/5 [00:00<?, ?it/s] 20%|██ | 1/5 [00:01<00:04, 1.22s/it] 40%|████ | 2/5 [00:02<00:03, 1.22s/it] 60%|██████ | 3/5 [00:03<00:02, 1.23s/it] 80%|████████ | 4/5 [00:04<00:01, 1.25s/it] 100%|██████████| 5/5 [00:05<00:00, 1.04s/it] 100%|██████████| 5/5 [00:05<00:00, 1.12s/it] Decoding latents in cuda:0... done in 0.55s Move latents to cpu... done in 0.0s 0: 480x640 1 face, 7.9ms Speed: 2.4ms preprocess, 7.9ms inference, 1.5ms postprocess per image at shape (1, 3, 480, 640) 0%| | 0/5 [00:00<?, ?it/s] 20%|██ | 1/5 [00:01<00:04, 1.24s/it] 40%|████ | 2/5 [00:02<00:03, 1.23s/it] 60%|██████ | 3/5 [00:03<00:02, 1.23s/it] 80%|████████ | 4/5 [00:04<00:01, 1.25s/it] 100%|██████████| 5/5 [00:05<00:00, 1.02s/it] 100%|██████████| 5/5 [00:05<00:00, 1.12s/it] Decoding latents in cuda:0... done in 0.55s Move latents to cpu... done in 0.0s Uploading outputs... Finished.