cjwbw/segmind-vegart 🔢📝 → 🖼️

▶️ 770 runs 📅 Dec 2023 ⚙️ Cog 0.8.6 🔗 GitHub ⚖️ License
fast-inference lcm-lora text-to-image

About

Fast Segmind-Vega with 2-8 inference steps.

Example Output

Prompt:

"Self-portrait oil painting, a beautiful cyborg with golden hair, 8k"

Output

Example output

Performance Metrics

2.04s Prediction Time
2.08s Total Time
All Input Parameters 
{
  "prompt": "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k",
  "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch)",
  "num_inference_steps": 4
}
Input Parameters
seed Type: integer
Random seed. Leave blank to randomize the seed
prompt Type: stringDefault: Self-portrait oil painting, a beautiful cyborg with golden hair, 8k
Input prompt
negative_prompt Type: stringDefault: (worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch)
Specify things to not see in the output
num_inference_steps Type: integerDefault: 4Range: 1 - 100
Number of denoising steps
Output Schema

Output

Type: string • Format: uri

Example Execution Logs 
Using seed: 12974
  0%|          | 0/4 [00:00<?, ?it/s]
 50%|█████     | 2/4 [00:00<00:00, 18.19it/s]
100%|██████████| 4/4 [00:00<00:00, 18.26it/s]
100%|██████████| 4/4 [00:00<00:00, 18.24it/s]
Version Details
Version ID
95be94f58749a793ad91388597f17882bb1bbc734daa892fc20fde789f9b1c01
Version Created
December 13, 2023
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