peter65374/sdxl-cat 🖼️🔢📝❓✓ → 🖼️
About
human-like cat sdxl-lora model

Example Output
Prompt:
"A photo of TOK, smiling cat walking on the hill"
Output

Performance Metrics
13.45s
Prediction Time
19.14s
Total Time
All Input Parameters
{ "width": 1024, "height": 1024, "prompt": "A photo of TOK, smiling cat walking on the hill", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 }
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: 92 Ensuring enough disk space... Free disk space: 1933190082560 Downloading weights: https://replicate.delivery/pbxt/MqZe51l1ASSuZKIVF843Z9ZAYynhaGYxtACGxaFv6wblJ7eRA/trained_model.tar b'Downloaded 186 MB bytes in 2.858s (65 MB/s)\nExtracted 186 MB in 0.066s (2.8 GB/s)\n' Downloaded weights in 3.2346155643463135 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: A photo of <s0><s1>, smiling cat walking on the hill txt2img mode 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:07, 3.72it/s] 7%|▋ | 2/30 [00:00<00:07, 3.71it/s] 10%|█ | 3/30 [00:00<00:07, 3.70it/s] 13%|█▎ | 4/30 [00:01<00:07, 3.70it/s] 17%|█▋ | 5/30 [00:01<00:06, 3.70it/s] 20%|██ | 6/30 [00:01<00:06, 3.70it/s] 23%|██▎ | 7/30 [00:01<00:06, 3.70it/s] 27%|██▋ | 8/30 [00:02<00:05, 3.71it/s] 30%|███ | 9/30 [00:02<00:05, 3.71it/s] 33%|███▎ | 10/30 [00:02<00:05, 3.71it/s] 37%|███▋ | 11/30 [00:02<00:05, 3.71it/s] 40%|████ | 12/30 [00:03<00:04, 3.71it/s] 43%|████▎ | 13/30 [00:03<00:04, 3.71it/s] 47%|████▋ | 14/30 [00:03<00:04, 3.71it/s] 50%|█████ | 15/30 [00:04<00:04, 3.71it/s] 53%|█████▎ | 16/30 [00:04<00:03, 3.71it/s] 57%|█████▋ | 17/30 [00:04<00:03, 3.70it/s] 60%|██████ | 18/30 [00:04<00:03, 3.71it/s] 63%|██████▎ | 19/30 [00:05<00:02, 3.70it/s] 67%|██████▋ | 20/30 [00:05<00:02, 3.70it/s] 70%|███████ | 21/30 [00:05<00:02, 3.70it/s] 73%|███████▎ | 22/30 [00:05<00:02, 3.70it/s] 77%|███████▋ | 23/30 [00:06<00:01, 3.70it/s] 80%|████████ | 24/30 [00:06<00:01, 3.70it/s] 83%|████████▎ | 25/30 [00:06<00:01, 3.70it/s] 87%|████████▋ | 26/30 [00:07<00:01, 3.70it/s] 90%|█████████ | 27/30 [00:07<00:00, 3.70it/s] 93%|█████████▎| 28/30 [00:07<00:00, 3.70it/s] 97%|█████████▋| 29/30 [00:07<00:00, 3.70it/s] 100%|██████████| 30/30 [00:08<00:00, 3.70it/s] 100%|██████████| 30/30 [00:08<00:00, 3.70it/s]
Version Details
- Version ID
0ac4841eb414b90346e08e27c48be8e3b03f6e8281d5844f965be8347614d2ed
- Version Created
- December 1, 2023