pilou57/piloupixar πΌοΈπ’πββ β πΌοΈ
About
modèle pour faire des images de femme cohérentes
Example Output
Prompt:
"TOK, a girl with brown hairs and green eyes, proportional human body and face, jumping off a cliff, diving, in a bikini, people at the top of the cliff are watching, highly detailed, hyper textured, 3D render, vivid and vibrant colors, modern pixar animation style"
Output
Performance Metrics
27.23s
Prediction Time
33.17s
Total Time
All Input Parameters
{
"width": 1024,
"height": 1024,
"prompt": "TOK, a girl with brown hairs and green eyes, proportional human body and face, jumping off a cliff, diving, in a bikini, people at the top of the cliff are watching, highly detailed, hyper textured, 3D render, vivid and vibrant colors, modern pixar animation style",
"refine": "expert_ensemble_refiner",
"scheduler": "K_EULER",
"lora_scale": 0.6,
"num_outputs": 1,
"guidance_scale": 9,
"apply_watermark": false,
"high_noise_frac": 0.8,
"negative_prompt": "sketch, flat, 2D, hand drawn",
"prompt_strength": 1,
"num_inference_steps": 40
}
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: 26794 Ensuring enough disk space... Free disk space: 2046162583552 Downloading weights: https://replicate.delivery/pbxt/TSUhvKh0f53AaSoFcwKsRMYTgM6ODznRz6DtgtMaynPfx60SA/trained_model.tar 2024-05-16T14:21:58Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/7bb3b7093b96bc1f url=https://replicate.delivery/pbxt/TSUhvKh0f53AaSoFcwKsRMYTgM6ODznRz6DtgtMaynPfx60SA/trained_model.tar 2024-05-16T14:22:11Z | INFO | [ Complete ] dest=/src/weights-cache/7bb3b7093b96bc1f size="186 MB" total_elapsed=13.060s url=https://replicate.delivery/pbxt/TSUhvKh0f53AaSoFcwKsRMYTgM6ODznRz6DtgtMaynPfx60SA/trained_model.tar b'' Downloaded weights in 13.242272138595581 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: <s0><s1>, a girl with brown hairs and green eyes, proportional human body and face, jumping off a cliff, diving, in a bikini, people at the top of the cliff are watching, highly detailed, hyper textured, 3D render, vivid and vibrant colors, modern pixar animation style txt2img mode 0%| | 0/32 [00:00<?, ?it/s] 3%|β | 1/32 [00:00<00:08, 3.62it/s] 6%|β | 2/32 [00:00<00:08, 3.61it/s] 9%|β | 3/32 [00:00<00:08, 3.61it/s] 12%|ββ | 4/32 [00:01<00:07, 3.61it/s] 16%|ββ | 5/32 [00:01<00:07, 3.60it/s] 19%|ββ | 6/32 [00:01<00:07, 3.60it/s] 22%|βββ | 7/32 [00:01<00:06, 3.60it/s] 25%|βββ | 8/32 [00:02<00:06, 3.59it/s] 28%|βββ | 9/32 [00:02<00:06, 3.59it/s] 31%|ββββ | 10/32 [00:02<00:06, 3.59it/s] 34%|ββββ | 11/32 [00:03<00:05, 3.59it/s] 38%|ββββ | 12/32 [00:03<00:05, 3.59it/s] 41%|ββββ | 13/32 [00:03<00:05, 3.60it/s] 44%|βββββ | 14/32 [00:03<00:05, 3.59it/s] 47%|βββββ | 15/32 [00:04<00:04, 3.59it/s] 50%|βββββ | 16/32 [00:04<00:04, 3.59it/s] 53%|ββββββ | 17/32 [00:04<00:04, 3.59it/s] 56%|ββββββ | 18/32 [00:05<00:03, 3.59it/s] 59%|ββββββ | 19/32 [00:05<00:03, 3.59it/s] 62%|βββββββ | 20/32 [00:05<00:03, 3.59it/s] 66%|βββββββ | 21/32 [00:05<00:03, 3.59it/s] 69%|βββββββ | 22/32 [00:06<00:02, 3.58it/s] 72%|ββββββββ | 23/32 [00:06<00:02, 3.58it/s] 75%|ββββββββ | 24/32 [00:06<00:02, 3.59it/s] 78%|ββββββββ | 25/32 [00:06<00:01, 3.59it/s] 81%|βββββββββ | 26/32 [00:07<00:01, 3.58it/s] 84%|βββββββββ | 27/32 [00:07<00:01, 3.58it/s] 88%|βββββββββ | 28/32 [00:07<00:01, 3.58it/s] 91%|βββββββββ | 29/32 [00:08<00:00, 3.58it/s] 94%|ββββββββββ| 30/32 [00:08<00:00, 3.58it/s] 97%|ββββββββββ| 31/32 [00:08<00:00, 3.59it/s] 100%|ββββββββββ| 32/32 [00:08<00:00, 3.59it/s] 100%|ββββββββββ| 32/32 [00:08<00:00, 3.59it/s] 0%| | 0/8 [00:00<?, ?it/s] 12%|ββ | 1/8 [00:00<00:01, 3.97it/s] 25%|βββ | 2/8 [00:00<00:01, 4.08it/s] 38%|ββββ | 3/8 [00:00<00:01, 4.11it/s] 50%|βββββ | 4/8 [00:00<00:00, 4.11it/s] 62%|βββββββ | 5/8 [00:01<00:00, 4.13it/s] 75%|ββββββββ | 6/8 [00:01<00:00, 4.13it/s] 88%|βββββββββ | 7/8 [00:01<00:00, 4.13it/s] 100%|ββββββββββ| 8/8 [00:01<00:00, 4.13it/s] 100%|ββββββββββ| 8/8 [00:01<00:00, 4.12it/s]
Version Details
- Version ID
b9072915f1db2ae1e47cb569fe48a67ed9c5441aea8cdc7b237ef9cb43ef82fd- Version Created
- May 16, 2024