9ness/7vinijotar 🖼️🔢❓📝✓ → 🖼️
About
IA Model of Vinicius JR with Real Madrid Jersey
Example Output
Prompt:
"Create a vivid and dynamic scene featuring 7vinijotar playing football on an improvised Brazilian street field. 7vinijotar is wearing a Real Madrid jersey, standing out as he showcases exceptional skill. The atmosphere is alive with the sounds of samba music and laughter, surrounded by vibrant colors and the energy of the neighborhood. Children and teenagers from the area challenge him, but 7vinijotar impresses everyone with breathtaking dribbles, tricks, and precise moves. Emphasize the joy, local culture, and the contrast of 7vinijotar's professional flair against the casual setting."
Output
Performance Metrics
7.94s
Prediction Time
7.96s
Total Time
All Input Parameters
{
"model": "dev",
"width": 810,
"height": 1440,
"prompt": "Create a vivid and dynamic scene featuring 7vinijotar playing football on an improvised Brazilian street field. 7vinijotar is wearing a Real Madrid jersey, standing out as he showcases exceptional skill. The atmosphere is alive with the sounds of samba music and laughter, surrounded by vibrant colors and the energy of the neighborhood. Children and teenagers from the area challenge him, but 7vinijotar impresses everyone with breathtaking dribbles, tricks, and precise moves. Emphasize the joy, local culture, and the contrast of 7vinijotar's professional flair against the casual setting.",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "9:16",
"output_format": "png",
"guidance_scale": 3.7,
"output_quality": 80,
"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
2024-12-20 11:24:24.447 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2024-12-20 11:24:24.447 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 93%|█████████▎| 282/304 [00:00<00:00, 2806.07it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2679.49it/s] 2024-12-20 11:24:24.561 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s free=28978401894400 Downloading weights 2024-12-20T11:24:24Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpju9kqic_/weights url=https://replicate.delivery/xezq/QlIAYV3EwuIgClh15oMBHWI3K87K9cAXwAzan2fTR90TFYeTA/trained_model.tar 2024-12-20T11:24:25Z | INFO | [ Complete ] dest=/tmp/tmpju9kqic_/weights size="172 MB" total_elapsed=1.349s url=https://replicate.delivery/xezq/QlIAYV3EwuIgClh15oMBHWI3K87K9cAXwAzan2fTR90TFYeTA/trained_model.tar Downloaded weights in 1.37s 2024-12-20 11:24:25.937 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/243c141c51eb4002 2024-12-20 11:24:26.011 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2024-12-20 11:24:26.012 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2024-12-20 11:24:26.012 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 93%|█████████▎| 282/304 [00:00<00:00, 2809.98it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2682.49it/s] 2024-12-20 11:24:26.125 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s Using seed: 19164 0it [00:00, ?it/s] 1it [00:00, 8.46it/s] 2it [00:00, 5.93it/s] 3it [00:00, 5.42it/s] 4it [00:00, 5.21it/s] 5it [00:00, 5.09it/s] 6it [00:01, 5.00it/s] 7it [00:01, 4.95it/s] 8it [00:01, 4.94it/s] 9it [00:01, 4.92it/s] 10it [00:01, 4.90it/s] 11it [00:02, 4.89it/s] 12it [00:02, 4.88it/s] 13it [00:02, 4.87it/s] 14it [00:02, 4.87it/s] 15it [00:02, 4.88it/s] 16it [00:03, 4.89it/s] 17it [00:03, 4.88it/s] 18it [00:03, 4.88it/s] 19it [00:03, 4.87it/s] 20it [00:04, 4.86it/s] 21it [00:04, 4.87it/s] 22it [00:04, 4.87it/s] 23it [00:04, 4.87it/s] 24it [00:04, 4.86it/s] 25it [00:05, 4.86it/s] 26it [00:05, 4.86it/s] 27it [00:05, 4.86it/s] 28it [00:05, 4.87it/s] 28it [00:05, 4.95it/s] Total safe images: 1 out of 1
Version Details
- Version ID
3a8c10db5cb84a42d3c2dff2e2685f7e7d7900435b75ce7f6ace6c2d3981c542- Version Created
- December 20, 2024