cjwbw/lambda-eclipse 🔢🖼️📝 → 🖼️
About
λ-ECLIPSE: Multi-Concept Personalized Text-to-Image Diffusion Models by Leveraging CLIP Latent Space
Example Output
Prompt:
"a cat wearing glasses at the beach"
Output
Performance Metrics
7.00s
Prediction Time
7.04s
Total Time
All Input Parameters
{
"image1": "https://replicate.delivery/pbxt/KNhvYb6Ux4ZbIu4C0W9W5Z2DDOkFvhwSl9h3O0zv8sbQuf5N/cat.png",
"image2": "https://replicate.delivery/pbxt/KNhvYqUGSU8ZuYWSX0UiJswZ0hLV63GSzeKT4CV0RRU1W4rc/blue_sunglasses.png",
"prompt": "a cat wearing glasses at the beach",
"guidance_scale": 4,
"negative_prompt": "over-exposure, under-exposure, saturated, duplicate, out of frame, lowres, cropped, worst quality, low quality, jpeg artifacts, morbid, mutilated, ugly, bad anatomy, bad proportions, deformed, blurry",
"subject_category1": "cat",
"subject_category2": "glasses",
"num_inference_steps": 50
}
Input Parameters
- seed
- Random seed. Leave blank to randomize the seed
- image1 (required)
- The image for the first subject.
- image2
- Optional. The image for the first subject.
- prompt
- The prompt to guide the image generation.
- guidance_scale
- Scale for classifier-free guidance.
- negative_prompt
- The prompt or prompts not to guide the image generation.
- subject_category1
- The subject category of the first image.
- subject_category2
- Optional. The subject category of the first image.
- num_inference_steps
- The number of denoising steps. More denoising steps usually lead to a higher quality image at the expense of slower inference.
Output Schema
Output
Example Execution Logs
Using seed: 50866 0%| | 0/50 [00:00<?, ?it/s] 4%|▍ | 2/50 [00:00<00:03, 12.38it/s] 8%|▊ | 4/50 [00:00<00:03, 12.44it/s] 12%|█▏ | 6/50 [00:00<00:03, 12.47it/s] 16%|█▌ | 8/50 [00:00<00:03, 12.49it/s] 20%|██ | 10/50 [00:00<00:03, 12.49it/s] 24%|██▍ | 12/50 [00:00<00:03, 12.52it/s] 28%|██▊ | 14/50 [00:01<00:02, 12.53it/s] 32%|███▏ | 16/50 [00:01<00:02, 12.56it/s] 36%|███▌ | 18/50 [00:01<00:02, 12.58it/s] 40%|████ | 20/50 [00:01<00:02, 12.60it/s] 44%|████▍ | 22/50 [00:01<00:02, 12.60it/s] 48%|████▊ | 24/50 [00:01<00:02, 12.55it/s] 52%|█████▏ | 26/50 [00:02<00:01, 12.56it/s] 56%|█████▌ | 28/50 [00:02<00:01, 12.58it/s] 60%|██████ | 30/50 [00:02<00:01, 12.59it/s] 64%|██████▍ | 32/50 [00:02<00:01, 12.58it/s] 68%|██████▊ | 34/50 [00:02<00:01, 12.60it/s] 72%|███████▏ | 36/50 [00:02<00:01, 12.61it/s] 76%|███████▌ | 38/50 [00:03<00:00, 12.61it/s] 80%|████████ | 40/50 [00:03<00:00, 12.61it/s] 84%|████████▍ | 42/50 [00:03<00:00, 12.61it/s] 88%|████████▊ | 44/50 [00:03<00:00, 12.61it/s] 92%|█████████▏| 46/50 [00:03<00:00, 12.60it/s] 96%|█████████▌| 48/50 [00:03<00:00, 12.60it/s] 100%|██████████| 50/50 [00:03<00:00, 12.60it/s] 100%|██████████| 50/50 [00:03<00:00, 12.57it/s]
Version Details
- Version ID
0e36b028d4ed70538c3e6ad369ebd2acf872b41e339b0adf1f6f7d095e248a55- Version Created
- February 10, 2024