tungsten-logo
Sign In
majicmix-alpha
majicmix-alpha

majicmix-alpha

13 stars
Version: v1.0-hq-controlnet
Input
prompt *
Input prompt
seed
Random seed. Set as -1 to randomize the seed
muscle
How muscular the person on the generated image should be
details
How much details the image should have
sampler
Sampler type
cfg_scale
Scale for classifier-free guidance
clip_skip
Whether to ignore the last layer of CLIP network or not
num_outputs
Number of output images
film_likeness
How film-like the generated image should be
samping_steps
Number of denoising steps
negative_prompt
Specify things to not see in the output
reference_image
Image with a reference architecture shape
image_dimensions
Pixel dimensions of output image (width x height)
Sign in to run this model for free!
Output
https://files.tungsten.run/uploads/6a0ddcf807e74f12b3ebe8488a0ddc72/tmpwj9v3b_n.png
https://files.tungsten.run/uploads/40f1d192763d4c1da280a3b3732d0995/tmpns13v2ev.png
https://files.tungsten.run/uploads/9640e73b7da84579b5b3d3cc605a2fcb/tmp0r77lidw.png
https://files.tungsten.run/uploads/5ab24d221a414fdd8f905e3b27f37459/tmp2op9eyn7.png
https://files.tungsten.run/uploads/5cf584376c3c43f2bece0b1011f2051f/tmp36y7l25z.png
https://files.tungsten.run/uploads/8d2c9252914f45a784ab2ae2ea36b58d/tmp2nh7p0s0.png
https://files.tungsten.run/uploads/5b3d906927c0435a995a444bc19246d2/tmp__eot7f9.png
https://files.tungsten.run/uploads/e1edda7f30164e64bc5a608f21005afb/tmpyn_4v9yy.png
This example was created by mjpyeon
Preparing inputs... Predicting... 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:08<02:40, 8.44s/it] 10%|█ | 2/20 [00:13<01:53, 6.32s/it] 15%|█▌ | 3/20 [00:18<01:36, 5.66s/it] 20%|██ | 4/20 [00:23<01:25, 5.36s/it] 25%|██▌ | 5/20 [00:27<01:18, 5.20s/it] 30%|███ | 6/20 [00:32<01:11, 5.11s/it] 35%|███▌ | 7/20 [00:37<01:05, 5.05s/it] 40%|████ | 8/20 [00:42<01:00, 5.01s/it] 45%|████▌ | 9/20 [00:47<00:54, 5.00s/it] 50%|█████ | 10/20 [00:52<00:49, 4.99s/it] 55%|█████▌ | 11/20 [00:57<00:44, 4.98s/it] 60%|██████ | 12/20 [01:02<00:39, 4.99s/it] 65%|██████▌ | 13/20 [01:07<00:35, 5.00s/it] 70%|███████ | 14/20 [01:12<00:29, 4.99s/it] 75%|███████▌ | 15/20 [01:17<00:24, 4.99s/it] 80%|████████ | 16/20 [01:22<00:19, 4.99s/it] 85%|████████▌ | 17/20 [01:27<00:15, 5.00s/it] 90%|█████████ | 18/20 [01:32<00:09, 5.00s/it] 95%|█████████▌| 19/20 [01:37<00:04, 5.00s/it] 100%|██████████| 20/20 [01:40<00:00, 4.25s/it] 100%|██████████| 20/20 [01:40<00:00, 5.01s/it] Prediction done.
prompt *
Input prompt
seed
Random seed. Set as -1 to randomize the seed
muscle
How muscular the person on the generated image should be
details
How much details the image should have
sampler
Sampler type
cfg_scale
Scale for classifier-free guidance
clip_skip
Whether to ignore the last layer of CLIP network or not
num_outputs
Number of output images
film_likeness
How film-like the generated image should be
samping_steps
Number of denoising steps
negative_prompt
Specify things to not see in the output
reference_image
Image with a reference architecture shape
image_dimensions
Pixel dimensions of output image (width x height)
Sign in to run this model for free!
https://files.tungsten.run/uploads/6a0ddcf807e74f12b3ebe8488a0ddc72/tmpwj9v3b_n.png
https://files.tungsten.run/uploads/40f1d192763d4c1da280a3b3732d0995/tmpns13v2ev.png
https://files.tungsten.run/uploads/9640e73b7da84579b5b3d3cc605a2fcb/tmp0r77lidw.png
https://files.tungsten.run/uploads/5ab24d221a414fdd8f905e3b27f37459/tmp2op9eyn7.png
https://files.tungsten.run/uploads/5cf584376c3c43f2bece0b1011f2051f/tmp36y7l25z.png
https://files.tungsten.run/uploads/8d2c9252914f45a784ab2ae2ea36b58d/tmp2nh7p0s0.png
https://files.tungsten.run/uploads/5b3d906927c0435a995a444bc19246d2/tmp__eot7f9.png
https://files.tungsten.run/uploads/e1edda7f30164e64bc5a608f21005afb/tmpyn_4v9yy.png
This example was created by mjpyeon
Preparing inputs... Predicting... 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:08<02:40, 8.44s/it] 10%|█ | 2/20 [00:13<01:53, 6.32s/it] 15%|█▌ | 3/20 [00:18<01:36, 5.66s/it] 20%|██ | 4/20 [00:23<01:25, 5.36s/it] 25%|██▌ | 5/20 [00:27<01:18, 5.20s/it] 30%|███ | 6/20 [00:32<01:11, 5.11s/it] 35%|███▌ | 7/20 [00:37<01:05, 5.05s/it] 40%|████ | 8/20 [00:42<01:00, 5.01s/it] 45%|████▌ | 9/20 [00:47<00:54, 5.00s/it] 50%|█████ | 10/20 [00:52<00:49, 4.99s/it] 55%|█████▌ | 11/20 [00:57<00:44, 4.98s/it] 60%|██████ | 12/20 [01:02<00:39, 4.99s/it] 65%|██████▌ | 13/20 [01:07<00:35, 5.00s/it] 70%|███████ | 14/20 [01:12<00:29, 4.99s/it] 75%|███████▌ | 15/20 [01:17<00:24, 4.99s/it] 80%|████████ | 16/20 [01:22<00:19, 4.99s/it] 85%|████████▌ | 17/20 [01:27<00:15, 5.00s/it] 90%|█████████ | 18/20 [01:32<00:09, 5.00s/it] 95%|█████████▌| 19/20 [01:37<00:04, 5.00s/it] 100%|██████████| 20/20 [01:40<00:00, 4.25s/it] 100%|██████████| 20/20 [01:40<00:00, 5.01s/it] Prediction done.