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A Walk on the Beach with CherrypickerXL-LCM
cherypickersxl-lcm:v0.2
sparks
sparks
·
Feb 3
370
Input
prompt
Specify things to see in the output
photo of a serene beach at sunset, with palm trees casting long shadows on the sand and waves gently lapping the shore, evoking a sense of peace and relaxation. A couple walks hand in hand along the water's edge, while seagulls glide gracefully overhead, capturing the calm beauty of a holiday farewell
negative_prompt
Specify things to not see in the output
num_outputs
Number of output images
3
width
Output image width
1200
height
Output image height
1200
enhance_face_with_adetailer
Enhance face with adetailer
false
enhance_hands_with_adetailer
Enhance hands with adetailer
false
adetailer_denoising_strength
1: completely redraw face or hands / 0: no effect on output images
0.55
detail
Enhance/diminish detail while keeping the overall style/character
1.5
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.
3690749373
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++ SDE Karras
samping_steps
Number of denoising steps
4
cfg_scale
Scale for classifier-free guidance
2
clip_skip
The number of last layers of CLIP network to skip
1
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/685811bfeeb74e659dcb1bdd02c6c5a9/00000-3690749373.webp
https://files.tungsten.run/uploads/f28aad39a2c249bdbb6f56ac947b78ac/00001-3690749374.webp
https://files.tungsten.run/uploads/387a8a8a2083498fb4aba7fecb22e943/00002-3690749375.webp
Finished in 27.1 seconds
Preparing inputs... Processing... Loading VAE weight: models/VAE/sdxl_vae.safetensors Full prompt: photo of a serene beach at sunset, with palm trees casting long shadows on the sand and waves gently lapping the shore, evoking a sense of peace and relaxation. A couple walks hand in hand along the water's edge, while seagulls glide gracefully overhead, capturing the calm beauty of a holiday farewell, <lora:add-detail-xl:1.5> Full negative prompt: 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:06<00:18, 6.33s/it] 50%|█████ | 2/4 [00:14<00:14, 7.49s/it] 75%|███████▌ | 3/4 [00:20<00:06, 6.74s/it] 100%|██████████| 4/4 [00:22<00:00, 4.89s/it] 100%|██████████| 4/4 [00:22<00:00, 5.63s/it] Decoding latents in cuda:0... done in 3.42s Move latents to cpu... done in 0.04s Uploading outputs... Finished.
prompt
Specify things to see in the output
photo of a serene beach at sunset, with palm trees casting long shadows on the sand and waves gently lapping the shore, evoking a sense of peace and relaxation. A couple walks hand in hand along the water's edge, while seagulls glide gracefully overhead, capturing the calm beauty of a holiday farewell
negative_prompt
Specify things to not see in the output
num_outputs
Number of output images
3
width
Output image width
1200
height
Output image height
1200
enhance_face_with_adetailer
Enhance face with adetailer
false
enhance_hands_with_adetailer
Enhance hands with adetailer
false
adetailer_denoising_strength
1: completely redraw face or hands / 0: no effect on output images
0.55
detail
Enhance/diminish detail while keeping the overall style/character
1.5
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.
3690749373
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++ SDE Karras
samping_steps
Number of denoising steps
4
cfg_scale
Scale for classifier-free guidance
2
clip_skip
The number of last layers of CLIP network to skip
1
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/685811bfeeb74e659dcb1bdd02c6c5a9/00000-3690749373.webp
https://files.tungsten.run/uploads/f28aad39a2c249bdbb6f56ac947b78ac/00001-3690749374.webp
https://files.tungsten.run/uploads/387a8a8a2083498fb4aba7fecb22e943/00002-3690749375.webp
Finished in 27.1 seconds
Preparing inputs... Processing... Loading VAE weight: models/VAE/sdxl_vae.safetensors Full prompt: photo of a serene beach at sunset, with palm trees casting long shadows on the sand and waves gently lapping the shore, evoking a sense of peace and relaxation. A couple walks hand in hand along the water's edge, while seagulls glide gracefully overhead, capturing the calm beauty of a holiday farewell, <lora:add-detail-xl:1.5> Full negative prompt: 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:06<00:18, 6.33s/it] 50%|█████ | 2/4 [00:14<00:14, 7.49s/it] 75%|███████▌ | 3/4 [00:20<00:06, 6.74s/it] 100%|██████████| 4/4 [00:22<00:00, 4.89s/it] 100%|██████████| 4/4 [00:22<00:00, 5.63s/it] Decoding latents in cuda:0... done in 3.42s Move latents to cpu... done in 0.04s Uploading outputs... Finished.