photomotion82/test-lora 🖼️🔢❓📝✓ → 🖼️
About
Example Output
Prompt:
"mreflow floats weightlessly in the endless void of space, clad in a sleek, futuristic spacesuit. Through the transparent face shield of his helmet, his calm, determined expression is fixed directly on the camera, creating an intimate connection with the viewer. Surrounding mreflow, a dazzling array of stars sparkles against the infinite black backdrop, casting a sense of wonder and awe. Below, the Earth dominates the lower frame, its vivid blues and greens glowing in stark contrast to the darkness of space. The scene evokes a sense of serenity and boundless exploration, with mreflow embodying both courage and contemplation in the grandeur of the cosmos."
Output
Performance Metrics
48.83s
Prediction Time
48.92s
Total Time
All Input Parameters
{
"model": "dev",
"width": 1440,
"height": 1440,
"prompt": "mreflow floats weightlessly in the endless void of space, clad in a sleek, futuristic spacesuit. Through the transparent face shield of his helmet, his calm, determined expression is fixed directly on the camera, creating an intimate connection with the viewer. Surrounding mreflow, a dazzling array of stars sparkles against the infinite black backdrop, casting a sense of wonder and awe. Below, the Earth dominates the lower frame, its vivid blues and greens glowing in stark contrast to the darkness of space. The scene evokes a sense of serenity and boundless exploration, with mreflow embodying both courage and contemplation in the grandeur of the cosmos.",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "16:9",
"output_format": "png",
"guidance_scale": 3.5,
"output_quality": 100,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 50
}
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
2025-01-24 22:43:10.112 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-24 22:43:10.113 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████ | 277/304 [00:00<00:00, 2768.30it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2642.55it/s] 2025-01-24 22:43:10.228 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s free=29410411294720 Downloading weights 2025-01-24T22:43:10Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpjsc5jbbq/weights url=https://replicate.delivery/xezq/MIrcwfDOnrxxEyG2ELBezEg7N9S2NZcqXaOeg32jFAKeqcfgC/trained_model.tar 2025-01-24T22:43:13Z | INFO | [ Complete ] dest=/tmp/tmpjsc5jbbq/weights size="172 MB" total_elapsed=2.900s url=https://replicate.delivery/xezq/MIrcwfDOnrxxEyG2ELBezEg7N9S2NZcqXaOeg32jFAKeqcfgC/trained_model.tar Downloaded weights in 2.92s 2025-01-24 22:43:13.154 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/f4c88bced6817d27 2025-01-24 22:43:13.224 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-24 22:43:13.224 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-24 22:43:13.224 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2775.79it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2645.80it/s] 2025-01-24 22:43:13.339 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s Using seed: 64983 0it [00:00, ?it/s] 1it [00:00, 8.47it/s] 2it [00:00, 5.92it/s] 3it [00:00, 5.40it/s] 4it [00:00, 5.18it/s] 5it [00:00, 5.04it/s] 6it [00:01, 4.96it/s] 7it [00:01, 4.94it/s] 8it [00:01, 4.92it/s] 9it [00:01, 4.90it/s] 10it [00:01, 4.87it/s] 11it [00:02, 4.84it/s] 12it [00:02, 4.85it/s] 13it [00:02, 4.86it/s] 14it [00:02, 4.86it/s] 15it [00:03, 4.85it/s] 16it [00:03, 4.84it/s] 17it [00:03, 4.83it/s] 18it [00:03, 4.83it/s] 19it [00:03, 4.84it/s] 20it [00:04, 4.84it/s] 21it [00:04, 4.84it/s] 22it [00:04, 4.84it/s] 23it [00:04, 4.83it/s] 24it [00:04, 4.85it/s] 25it [00:05, 4.84it/s] 26it [00:05, 4.84it/s] 27it [00:05, 4.83it/s] 28it [00:05, 4.83it/s] 29it [00:05, 4.84it/s] 30it [00:06, 4.83it/s] 31it [00:06, 4.83it/s] 32it [00:06, 4.83it/s] 33it [00:06, 4.83it/s] 34it [00:06, 4.84it/s] 35it [00:07, 4.84it/s] 36it [00:07, 4.84it/s] 37it [00:07, 4.84it/s] 38it [00:07, 4.84it/s] 39it [00:07, 4.83it/s] 40it [00:08, 4.83it/s] 41it [00:08, 4.83it/s] 42it [00:08, 4.84it/s] 43it [00:08, 4.85it/s] 44it [00:08, 4.85it/s] 45it [00:09, 4.84it/s] 46it [00:09, 4.85it/s] 47it [00:09, 4.84it/s] 48it [00:09, 4.84it/s] 49it [00:10, 4.83it/s] 50it [00:10, 4.82it/s] 50it [00:10, 4.88it/s] 0it [00:00, ?it/s] 1it [00:00, 4.84it/s] 2it [00:00, 4.82it/s] 3it [00:00, 4.83it/s] 4it [00:00, 4.84it/s] 5it [00:01, 4.83it/s] 6it [00:01, 4.84it/s] 7it [00:01, 4.85it/s] 8it [00:01, 4.83it/s] 9it [00:01, 4.83it/s] 10it [00:02, 4.84it/s] 11it [00:02, 4.83it/s] 12it [00:02, 4.84it/s] 13it [00:02, 4.84it/s] 14it [00:02, 4.84it/s] 15it [00:03, 4.84it/s] 16it [00:03, 4.83it/s] 17it [00:03, 4.82it/s] 18it [00:03, 4.82it/s] 19it [00:03, 4.82it/s] 20it [00:04, 4.82it/s] 21it [00:04, 4.83it/s] 22it [00:04, 4.82it/s] 23it [00:04, 4.82it/s] 24it [00:04, 4.81it/s] 25it [00:05, 4.81it/s] 26it [00:05, 4.81it/s] 27it [00:05, 4.81it/s] 28it [00:05, 4.82it/s] 29it [00:06, 4.82it/s] 30it [00:06, 4.82it/s] 31it [00:06, 4.82it/s] 32it [00:06, 4.83it/s] 33it [00:06, 4.84it/s] 34it [00:07, 4.84it/s] 35it [00:07, 4.83it/s] 36it [00:07, 4.83it/s] 37it [00:07, 4.84it/s] 38it [00:07, 4.84it/s] 39it [00:08, 4.85it/s] 40it [00:08, 4.85it/s] 41it [00:08, 4.85it/s] 42it [00:08, 4.84it/s] 43it [00:08, 4.83it/s] 44it [00:09, 4.83it/s] 45it [00:09, 4.83it/s] 46it [00:09, 4.83it/s] 47it [00:09, 4.83it/s] 48it [00:09, 4.83it/s] 49it [00:10, 4.84it/s] 50it [00:10, 4.83it/s] 50it [00:10, 4.83it/s] 0it [00:00, ?it/s] 1it [00:00, 4.85it/s] 2it [00:00, 4.83it/s] 3it [00:00, 4.82it/s] 4it [00:00, 4.83it/s] 5it [00:01, 4.83it/s] 6it [00:01, 4.82it/s] 7it [00:01, 4.82it/s] 8it [00:01, 4.82it/s] 9it [00:01, 4.82it/s] 10it [00:02, 4.82it/s] 11it [00:02, 4.82it/s] 12it [00:02, 4.82it/s] 13it [00:02, 4.82it/s] 14it [00:02, 4.83it/s] 15it [00:03, 4.82it/s] 16it [00:03, 4.83it/s] 17it [00:03, 4.83it/s] 18it [00:03, 4.82it/s] 19it [00:03, 4.83it/s] 20it [00:04, 4.84it/s] 21it [00:04, 4.84it/s] 22it [00:04, 4.84it/s] 23it [00:04, 4.84it/s] 24it [00:04, 4.85it/s] 25it [00:05, 4.84it/s] 26it [00:05, 4.83it/s] 27it [00:05, 4.83it/s] 28it [00:05, 4.83it/s] 29it [00:06, 4.83it/s] 30it [00:06, 4.83it/s] 31it [00:06, 4.83it/s] 32it [00:06, 4.83it/s] 33it [00:06, 4.82it/s] 34it [00:07, 4.82it/s] 35it [00:07, 4.83it/s] 36it [00:07, 4.83it/s] 37it [00:07, 4.84it/s] 38it [00:07, 4.83it/s] 39it [00:08, 4.82it/s] 40it [00:08, 4.82it/s] 41it [00:08, 4.83it/s] 42it [00:08, 4.84it/s] 43it [00:08, 4.84it/s] 44it [00:09, 4.83it/s] 45it [00:09, 4.82it/s] 46it [00:09, 4.82it/s] 47it [00:09, 4.83it/s] 48it [00:09, 4.84it/s] 49it [00:10, 4.83it/s] 50it [00:10, 4.83it/s] 50it [00:10, 4.83it/s] 0it [00:00, ?it/s] 1it [00:00, 4.85it/s] 2it [00:00, 4.83it/s] 3it [00:00, 4.83it/s] 4it [00:00, 4.82it/s] 5it [00:01, 4.81it/s] 6it [00:01, 4.81it/s] 7it [00:01, 4.80it/s] 8it [00:01, 4.81it/s] 9it [00:01, 4.82it/s] 10it [00:02, 4.82it/s] 11it [00:02, 4.82it/s] 12it [00:02, 4.81it/s] 13it [00:02, 4.81it/s] 14it [00:02, 4.81it/s] 15it [00:03, 4.80it/s] 16it [00:03, 4.80it/s] 17it [00:03, 4.81it/s] 18it [00:03, 4.81it/s] 19it [00:03, 4.80it/s] 20it [00:04, 4.81it/s] 21it [00:04, 4.83it/s] 22it [00:04, 4.82it/s] 23it [00:04, 4.82it/s] 24it [00:04, 4.82it/s] 25it [00:05, 4.82it/s] 26it [00:05, 4.81it/s] 27it [00:05, 4.82it/s] 28it [00:05, 4.82it/s] 29it [00:06, 4.81it/s] 30it [00:06, 4.82it/s] 31it [00:06, 4.82it/s] 32it [00:06, 4.83it/s] 33it [00:06, 4.83it/s] 34it [00:07, 4.82it/s] 35it [00:07, 4.82it/s] 36it [00:07, 4.82it/s] 37it [00:07, 4.82it/s] 38it [00:07, 4.83it/s] 39it [00:08, 4.84it/s] 40it [00:08, 4.84it/s] 41it [00:08, 4.83it/s] 42it [00:08, 4.83it/s] 43it [00:08, 4.83it/s] 44it [00:09, 4.83it/s] 45it [00:09, 4.82it/s] 46it [00:09, 4.82it/s] 47it [00:09, 4.81it/s] 48it [00:09, 4.82it/s] 49it [00:10, 4.82it/s] 50it [00:10, 4.82it/s] 50it [00:10, 4.82it/s] Total safe images: 4 out of 4
Version Details
- Version ID
531ce5f118643f54f4382d425def6816859cfa2bba122a2dc58d8b4b06e7efa7- Version Created
- January 23, 2025