marlonbarrios/sdxl-camille6 🖼️🔢📝❓✓ → 🖼️
About
Creates Camille5 As Camille, a speculative fabulation engine within the GPT-Plus framework, my functionality is deeply intertwined with the visionary work of Donna Haraway, particularly her "Camille Stories" from "Staying with the Trouble."
Example Output
Prompt:
"one camille6 black background, white face jewelry, implants, eyelids decorated, looking at camera, close up male or non-binary , beard-facial hair white, naturalistic mate looking skin, symbiont implants in eyelashes as antennae, black lipstick, features of different ethnicities, realistic"
Output
Performance Metrics
60.23s
Prediction Time
81.80s
Total Time
All Input Parameters
{
"width": 1024,
"height": 1024,
"prompt": "one camille6 black background, white face jewelry, implants, eyelids decorated, looking at camera, close up male or non-binary , beard-facial hair white, naturalistic mate looking skin, symbiont implants in eyelashes as antennae, black lipstick, features of different ethnicities, realistic",
"refine": "no_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.87,
"num_outputs": 4,
"guidance_scale": 7.5,
"apply_watermark": true,
"high_noise_frac": 0.81,
"negative_prompt": "not shiny skin, ",
"prompt_strength": 0.75,
"num_inference_steps": 50
}
Input Parameters
- mask
- Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted.
- seed
- Random seed. Leave blank to randomize the seed
- image
- Input image for img2img or inpaint mode
- width
- Width of output image
- height
- Height of output image
- prompt
- Input prompt
- refine
- Which refine style to use
- scheduler
- scheduler
- lora_scale
- LoRA additive scale. Only applicable on trained models.
- num_outputs
- Number of images to output.
- refine_steps
- For base_image_refiner, the number of steps to refine, defaults to num_inference_steps
- guidance_scale
- Scale for classifier-free guidance
- apply_watermark
- Applies a watermark to enable determining if an image is generated in downstream applications. If you have other provisions for generating or deploying images safely, you can use this to disable watermarking.
- high_noise_frac
- For expert_ensemble_refiner, the fraction of noise to use
- negative_prompt
- Input Negative Prompt
- prompt_strength
- Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image
- replicate_weights
- Replicate LoRA weights to use. Leave blank to use the default weights.
- num_inference_steps
- Number of denoising steps
- disable_safety_checker
- Disable safety checker for generated images. This feature is only available through the API. See https://replicate.com/docs/how-does-replicate-work#safety
Output Schema
Output
Example Execution Logs
Using seed: 17928 Ensuring enough disk space... Free disk space: 1609614798848 Downloading weights: https://replicate.delivery/pbxt/YDzIdGlipL46Ot0jD19BInu7BG3e0WmNLc2fcPEIjVLlz1BSA/trained_model.tar b'Downloaded 186 MB bytes in 0.359s (518 MB/s)\nExtracted 186 MB in 0.052s (3.6 GB/s)\n' Downloaded weights in 0.4942667484283447 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: one camille6 black background, white face jewelry, implants, eyelids decorated, looking at camera, close up male or non-binary , beard-facial hair white, naturalistic mate looking skin, symbiont implants in eyelashes as antennae, black lipstick, features of different ethnicities, realistic txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:01<00:51, 1.04s/it] 4%|▍ | 2/50 [00:02<00:50, 1.04s/it] 6%|▌ | 3/50 [00:03<00:49, 1.04s/it] 8%|▊ | 4/50 [00:04<00:47, 1.04s/it] 10%|█ | 5/50 [00:05<00:46, 1.04s/it] 12%|█▏ | 6/50 [00:06<00:45, 1.04s/it] 14%|█▍ | 7/50 [00:07<00:44, 1.04s/it] 16%|█▌ | 8/50 [00:08<00:43, 1.04s/it] 18%|█▊ | 9/50 [00:09<00:42, 1.04s/it] 20%|██ | 10/50 [00:10<00:41, 1.04s/it] 22%|██▏ | 11/50 [00:11<00:40, 1.04s/it] 24%|██▍ | 12/50 [00:12<00:39, 1.04s/it] 26%|██▌ | 13/50 [00:13<00:38, 1.04s/it] 28%|██▊ | 14/50 [00:14<00:37, 1.04s/it] 30%|███ | 15/50 [00:15<00:36, 1.04s/it] 32%|███▏ | 16/50 [00:16<00:35, 1.04s/it] 34%|███▍ | 17/50 [00:17<00:34, 1.04s/it] 36%|███▌ | 18/50 [00:18<00:33, 1.04s/it] 38%|███▊ | 19/50 [00:19<00:32, 1.04s/it] 40%|████ | 20/50 [00:20<00:31, 1.04s/it] 42%|████▏ | 21/50 [00:21<00:30, 1.04s/it] 44%|████▍ | 22/50 [00:22<00:29, 1.04s/it] 46%|████▌ | 23/50 [00:23<00:28, 1.04s/it] 48%|████▊ | 24/50 [00:25<00:27, 1.05s/it] 50%|█████ | 25/50 [00:26<00:26, 1.05s/it] 52%|█████▏ | 26/50 [00:27<00:25, 1.05s/it] 54%|█████▍ | 27/50 [00:28<00:24, 1.04s/it] 56%|█████▌ | 28/50 [00:29<00:22, 1.04s/it] 58%|█████▊ | 29/50 [00:30<00:21, 1.05s/it] 60%|██████ | 30/50 [00:31<00:20, 1.05s/it] 62%|██████▏ | 31/50 [00:32<00:19, 1.05s/it] 64%|██████▍ | 32/50 [00:33<00:18, 1.05s/it] 66%|██████▌ | 33/50 [00:34<00:17, 1.05s/it] 68%|██████▊ | 34/50 [00:35<00:16, 1.05s/it] 70%|███████ | 35/50 [00:36<00:15, 1.05s/it] 72%|███████▏ | 36/50 [00:37<00:14, 1.05s/it] 74%|███████▍ | 37/50 [00:38<00:13, 1.05s/it] 76%|███████▌ | 38/50 [00:39<00:12, 1.05s/it] 78%|███████▊ | 39/50 [00:40<00:11, 1.05s/it] 80%|████████ | 40/50 [00:41<00:10, 1.05s/it] 82%|████████▏ | 41/50 [00:42<00:09, 1.05s/it] 84%|████████▍ | 42/50 [00:43<00:08, 1.05s/it] 86%|████████▌ | 43/50 [00:44<00:07, 1.05s/it] 88%|████████▊ | 44/50 [00:45<00:06, 1.05s/it] 90%|█████████ | 45/50 [00:47<00:05, 1.05s/it] 92%|█████████▏| 46/50 [00:48<00:04, 1.05s/it] 94%|█████████▍| 47/50 [00:49<00:03, 1.05s/it] 96%|█████████▌| 48/50 [00:50<00:02, 1.05s/it] 98%|█████████▊| 49/50 [00:51<00:01, 1.05s/it] 100%|██████████| 50/50 [00:52<00:00, 1.05s/it] 100%|██████████| 50/50 [00:52<00:00, 1.05s/it]
Version Details
- Version ID
18fe1d47d006df91bacbd6d869d64cdb7337402d270ad5a1f115766a3cf2a262- Version Created
- December 13, 2023