fofr/sdxl-energy-drink 🖼️🔢📝❓✓ → 🖼️
About
SDXL fine-tuned on energy drink designs
Example Output
Prompt:
"A photo of a TOK energy drinks can, Super Mario themed, white background"
Output
Performance Metrics
15.86s
Prediction Time
22.17s
Total Time
All Input Parameters
{
"width": 1024,
"height": 1024,
"prompt": "A photo of a TOK energy drinks can, Super Mario themed, white background",
"refine": "no_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.6,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": false,
"high_noise_frac": 0.8,
"negative_prompt": "text, words,",
"prompt_strength": 0.8,
"num_inference_steps": 25
}
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: 27407 Ensuring enough disk space... Free disk space: 1945079513088 Downloading weights: https://replicate.delivery/pbxt/1YQb0H6kYCqKD9XwE9CEZj4KxuUh0epmZg1r20AeaiXTyBLSA/trained_model.tar 2024-01-10T10:01:37Z | INFO | [ Initiating ] dest=/src/weights-cache/1075171f2b09d76f minimum_chunk_size=150M url=https://replicate.delivery/pbxt/1YQb0H6kYCqKD9XwE9CEZj4KxuUh0epmZg1r20AeaiXTyBLSA/trained_model.tar 2024-01-10T10:01:43Z | INFO | [ Complete ] dest=/src/weights-cache/1075171f2b09d76f size="186 MB" total_elapsed=6.539s url=https://replicate.delivery/pbxt/1YQb0H6kYCqKD9XwE9CEZj4KxuUh0epmZg1r20AeaiXTyBLSA/trained_model.tar b'' Downloaded weights in 6.714761734008789 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: A photo of a <s0><s1> energy drinks can, Super Mario themed, white background txt2img mode 0%| | 0/25 [00:00<?, ?it/s] 4%|▍ | 1/25 [00:00<00:06, 3.68it/s] 8%|▊ | 2/25 [00:00<00:06, 3.68it/s] 12%|█▏ | 3/25 [00:00<00:05, 3.68it/s] 16%|█▌ | 4/25 [00:01<00:05, 3.68it/s] 20%|██ | 5/25 [00:01<00:05, 3.67it/s] 24%|██▍ | 6/25 [00:01<00:05, 3.68it/s] 28%|██▊ | 7/25 [00:01<00:04, 3.68it/s] 32%|███▏ | 8/25 [00:02<00:04, 3.68it/s] 36%|███▌ | 9/25 [00:02<00:04, 3.68it/s] 40%|████ | 10/25 [00:02<00:04, 3.68it/s] 44%|████▍ | 11/25 [00:02<00:03, 3.68it/s] 48%|████▊ | 12/25 [00:03<00:03, 3.67it/s] 52%|█████▏ | 13/25 [00:03<00:03, 3.68it/s] 56%|█████▌ | 14/25 [00:03<00:02, 3.67it/s] 60%|██████ | 15/25 [00:04<00:02, 3.67it/s] 64%|██████▍ | 16/25 [00:04<00:02, 3.67it/s] 68%|██████▊ | 17/25 [00:04<00:02, 3.67it/s] 72%|███████▏ | 18/25 [00:04<00:01, 3.66it/s] 76%|███████▌ | 19/25 [00:05<00:01, 3.66it/s] 80%|████████ | 20/25 [00:05<00:01, 3.66it/s] 84%|████████▍ | 21/25 [00:05<00:01, 3.66it/s] 88%|████████▊ | 22/25 [00:05<00:00, 3.66it/s] 92%|█████████▏| 23/25 [00:06<00:00, 3.66it/s] 96%|█████████▌| 24/25 [00:06<00:00, 3.66it/s] 100%|██████████| 25/25 [00:06<00:00, 3.66it/s] 100%|██████████| 25/25 [00:06<00:00, 3.67it/s]
Version Details
- Version ID
4bf3a3032664de2ba70247b3858f6a31569edec83dfabf6cf60cb98224a110dd- Version Created
- January 10, 2024