lucataco/realvisxl2-lora-inference 🖼️🔢📝❓✓ → 🖼️
About
POC to run inference on Realvisxl2 LoRAs
Example Output
Prompt:
"A photo of TOK"
Output
Performance Metrics
25.24s
Prediction Time
115.75s
Total Time
All Input Parameters
{
"seed": 6995,
"width": 1024,
"height": 1024,
"prompt": "A photo of TOK",
"refine": "no_refiner",
"lora_url": "https://replicate.delivery/pbxt/L5zHkM0OHX4ZF1Ipnaiok6GHGvrRgZHBqbz2JjtBAtWz8mdE/trained_model.tar",
"scheduler": "DPMSolverMultistep",
"lora_scale": 0.6,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": true,
"high_noise_frac": 0.8,
"negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth",
"prompt_strength": 0.8,
"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
- lora_url (required)
- Load Lora model
- 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
- num_inference_steps
- Number of denoising steps
Output Schema
Output
Example Execution Logs
LORA
Loading ssd txt2img pipeline...
Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]
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Loading pipeline components...: 100%|██████████| 7/7 [00:01<00:00, 6.97it/s]
Loading ssd lora weights...
Loading fine-tuned model
Does not have Unet. Assume we are using LoRA
Loading Unet LoRA
Using seed: 6995
Prompt: A photo of <s0><s1>
txt2img mode
0%| | 0/50 [00:00<?, ?it/s]/root/.pyenv/versions/3.11.6/lib/python3.11/site-packages/diffusers/models/attention_processor.py:1815: FutureWarning: `LoRAAttnProcessor2_0` is deprecated and will be removed in version 0.26.0. Make sure use AttnProcessor2_0 instead by settingLoRA layers to `self.{to_q,to_k,to_v,to_out[0]}.lora_layer` respectively. This will be done automatically when using `LoraLoaderMixin.load_lora_weights`
deprecate(
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Version Details
- Version ID
9b5a0c77cd4f6bdb53a2c3d05b4774df02876d21dd7d37f13f518c03e996945b- Version Created
- November 8, 2023