yacinesy/dh1212 🖼️🔢❓📝✓ → 🖼️
About
Example Output
Prompt:
"A stylish man walks confidently down an outdoor cobblestone street, dressed in an impeccably tailored dark blue three-piece suit. The suit is paired with a crisp white dress shirt and a rich burgundy tie, along with a matching pocket square in the jacket. His polished brown leather dress shoes add a touch of sophistication to the ensemble. The scene takes place in an elegant urban environment, with classic old buildings and cars parked along the sides, emphasizing the refined and upscale atmosphere of the exterior setting"
Output
Performance Metrics
25.39s
Prediction Time
25.40s
Total Time
All Input Parameters
{
"model": "dev",
"prompt": "A stylish man walks confidently down an outdoor cobblestone street, dressed in an impeccably tailored dark blue three-piece suit. The suit is paired with a crisp white dress shirt and a rich burgundy tie, along with a matching pocket square in the jacket. His polished brown leather dress shoes add a touch of sophistication to the ensemble. The scene takes place in an elegant urban environment, with classic old buildings and cars parked along the sides, emphasizing the refined and upscale atmosphere of the exterior setting",
"lora_scale": 1,
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3.5,
"output_quality": 90,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}
Input Parameters
- mask
- Image mask for image inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
- seed
- Random seed. Set for reproducible generation
- image
- Input image for image to image or inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
- model
- Which model to run inference with. The dev model performs best with around 28 inference steps but the schnell model only needs 4 steps.
- width
- Width of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation
- height
- Height of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation
- prompt (required)
- Prompt for generated image. If you include the `trigger_word` used in the training process you are more likely to activate the trained object, style, or concept in the resulting image.
- go_fast
- Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16
- extra_lora
- Load LoRA weights. Supports Replicate models in the format <owner>/<username> or <owner>/<username>/<version>, HuggingFace URLs in the format huggingface.co/<owner>/<model-name>, CivitAI URLs in the format civitai.com/models/<id>[/<model-name>], or arbitrary .safetensors URLs from the Internet. For example, 'fofr/flux-pixar-cars'
- lora_scale
- Determines how strongly the main LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.
- megapixels
- Approximate number of megapixels for generated image
- num_outputs
- Number of outputs to generate
- aspect_ratio
- Aspect ratio for the generated image. If custom is selected, uses height and width below & will run in bf16 mode
- output_format
- Format of the output images
- guidance_scale
- Guidance scale for the diffusion process. Lower values can give more realistic images. Good values to try are 2, 2.5, 3 and 3.5
- output_quality
- Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs
- prompt_strength
- Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image
- extra_lora_scale
- Determines how strongly the extra LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.
- replicate_weights
- Load LoRA weights. Supports Replicate models in the format <owner>/<username> or <owner>/<username>/<version>, HuggingFace URLs in the format huggingface.co/<owner>/<model-name>, CivitAI URLs in the format civitai.com/models/<id>[/<model-name>], or arbitrary .safetensors URLs from the Internet. For example, 'fofr/flux-pixar-cars'
- num_inference_steps
- Number of denoising steps. More steps can give more detailed images, but take longer.
- disable_safety_checker
- Disable safety checker for generated images.
Output Schema
Output
Example Execution Logs
Using seed: 40938 Prompt: A stylish man walks confidently down an outdoor cobblestone street, dressed in an impeccably tailored dark blue three-piece suit. The suit is paired with a crisp white dress shirt and a rich burgundy tie, along with a matching pocket square in the jacket. His polished brown leather dress shoes add a touch of sophistication to the ensemble. The scene takes place in an elegant urban environment, with classic old buildings and cars parked along the sides, emphasizing the refined and upscale atmosphere of the exterior setting [!] txt2img mode Using dev model free=8034403946496 Downloading weights 2024-09-15T21:25:25Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp0qrvvnc7/weights url=https://replicate.delivery/yhqm/svpzcMJj3LJWA90gwDl5UD301wb0MHWdleUgGRd9mfpP1OdTA/trained_model.tar 2024-09-15T21:25:27Z | INFO | [ Complete ] dest=/tmp/tmp0qrvvnc7/weights size="516 MB" total_elapsed=1.902s url=https://replicate.delivery/yhqm/svpzcMJj3LJWA90gwDl5UD301wb0MHWdleUgGRd9mfpP1OdTA/trained_model.tar Downloaded weights in 1.95s Loaded LoRAs in 17.13s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.52it/s] 7%|▋ | 2/28 [00:00<00:06, 3.97it/s] 11%|█ | 3/28 [00:00<00:06, 3.75it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.65it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.60it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.57it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.55it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.54it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.53it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.53it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.52it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.52it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.52it/s] 50%|█████ | 14/28 [00:03<00:03, 3.52it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.52it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.51it/s] 61%|██████ | 17/28 [00:04<00:03, 3.51it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.51it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.51it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.51it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.51it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.51it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.51it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.51it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.51it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.51it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.51it/s] 100%|██████████| 28/28 [00:07<00:00, 3.51it/s] 100%|██████████| 28/28 [00:07<00:00, 3.54it/s]
Version Details
- Version ID
ad92f2abaf72d29f0906931b2ee85d47cf24c297835a6e07487e8d55864e3375- Version Created
- September 15, 2024