iamprofessorex/helldivers2-skull-logo 🖼️🔢❓📝✓ → 🖼️
About

Example Output
Prompt:
"a detailed tactical military vest, futuristic design, matte black material, HELLDIVERS2SKULLLOGO skull logo emblazoned on the chest plate, high quality material, military grade, photorealistic, 8k, detailed fabric texture, ambient lighting"
Output




Performance Metrics
27.18s
Prediction Time
27.24s
Total Time
All Input Parameters
{ "model": "dev", "prompt": "a detailed tactical military vest, futuristic design, matte black material, HELLDIVERS2SKULLLOGO skull logo emblazoned on the chest plate, high quality material, military grade, photorealistic, 8k, detailed fabric texture, ambient lighting", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "png", "guidance_scale": 3, "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
2025-01-28 21:57:39.102 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-28 21:57:39.103 | 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, 2761.10it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2678.13it/s] 2025-01-28 21:57:39.216 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s free=28835000127488 Downloading weights 2025-01-28T21:57:39Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpja0yx7js/weights url=https://replicate.delivery/xezq/6WvLF9W4ImIVEVAPZ2FwTKbX3eGDn55vupQuq15jPIcIF4EKA/trained_model.tar 2025-01-28T21:57:41Z | INFO | [ Complete ] dest=/tmp/tmpja0yx7js/weights size="172 MB" total_elapsed=1.898s url=https://replicate.delivery/xezq/6WvLF9W4ImIVEVAPZ2FwTKbX3eGDn55vupQuq15jPIcIF4EKA/trained_model.tar Downloaded weights in 1.92s 2025-01-28 21:57:41.140 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/c0d147d239d01e79 2025-01-28 21:57:41.212 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-28 21:57:41.212 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-28 21:57:41.212 | 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, 2764.43it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2681.24it/s] 2025-01-28 21:57:41.326 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s Using seed: 51439 0it [00:00, ?it/s] 1it [00:00, 8.31it/s] 2it [00:00, 5.81it/s] 3it [00:00, 5.29it/s] 4it [00:00, 5.08it/s] 5it [00:00, 4.95it/s] 6it [00:01, 4.88it/s] 7it [00:01, 4.84it/s] 8it [00:01, 4.83it/s] 9it [00:01, 4.81it/s] 10it [00:02, 4.78it/s] 11it [00:02, 4.76it/s] 12it [00:02, 4.76it/s] 13it [00:02, 4.77it/s] 14it [00:02, 4.77it/s] 15it [00:03, 4.76it/s] 16it [00:03, 4.74it/s] 17it [00:03, 4.74it/s] 18it [00:03, 4.75it/s] 19it [00:03, 4.75it/s] 20it [00:04, 4.76it/s] 21it [00:04, 4.75it/s] 22it [00:04, 4.75it/s] 23it [00:04, 4.76it/s] 24it [00:04, 4.76it/s] 25it [00:05, 4.76it/s] 26it [00:05, 4.76it/s] 27it [00:05, 4.75it/s] 28it [00:05, 4.76it/s] 28it [00:05, 4.83it/s] 0it [00:00, ?it/s] 1it [00:00, 4.80it/s] 2it [00:00, 4.78it/s] 3it [00:00, 4.76it/s] 4it [00:00, 4.75it/s] 5it [00:01, 4.75it/s] 6it [00:01, 4.75it/s] 7it [00:01, 4.75it/s] 8it [00:01, 4.75it/s] 9it [00:01, 4.75it/s] 10it [00:02, 4.75it/s] 11it [00:02, 4.75it/s] 12it [00:02, 4.75it/s] 13it [00:02, 4.75it/s] 14it [00:02, 4.76it/s] 15it [00:03, 4.76it/s] 16it [00:03, 4.76it/s] 17it [00:03, 4.75it/s] 18it [00:03, 4.74it/s] 19it [00:03, 4.74it/s] 20it [00:04, 4.73it/s] 21it [00:04, 4.74it/s] 22it [00:04, 4.74it/s] 23it [00:04, 4.75it/s] 24it [00:05, 4.75it/s] 25it [00:05, 4.74it/s] 26it [00:05, 4.75it/s] 27it [00:05, 4.74it/s] 28it [00:05, 4.75it/s] 28it [00:05, 4.75it/s] 0it [00:00, ?it/s] 1it [00:00, 4.80it/s] 2it [00:00, 4.76it/s] 3it [00:00, 4.75it/s] 4it [00:00, 4.75it/s] 5it [00:01, 4.74it/s] 6it [00:01, 4.76it/s] 7it [00:01, 4.75it/s] 8it [00:01, 4.74it/s] 9it [00:01, 4.74it/s] 10it [00:02, 4.73it/s] 11it [00:02, 4.74it/s] 12it [00:02, 4.74it/s] 13it [00:02, 4.73it/s] 14it [00:02, 4.74it/s] 15it [00:03, 4.74it/s] 16it [00:03, 4.74it/s] 17it [00:03, 4.74it/s] 18it [00:03, 4.74it/s] 19it [00:04, 4.72it/s] 20it [00:04, 4.72it/s] 21it [00:04, 4.73it/s] 22it [00:04, 4.74it/s] 23it [00:04, 4.74it/s] 24it [00:05, 4.74it/s] 25it [00:05, 4.74it/s] 26it [00:05, 4.74it/s] 27it [00:05, 4.73it/s] 28it [00:05, 4.73it/s] 28it [00:05, 4.74it/s] 0it [00:00, ?it/s] 1it [00:00, 4.79it/s] 2it [00:00, 4.75it/s] 3it [00:00, 4.74it/s] 4it [00:00, 4.75it/s] 5it [00:01, 4.76it/s] 6it [00:01, 4.75it/s] 7it [00:01, 4.74it/s] 8it [00:01, 4.74it/s] 9it [00:01, 4.75it/s] 10it [00:02, 4.74it/s] 11it [00:02, 4.74it/s] 12it [00:02, 4.74it/s] 13it [00:02, 4.74it/s] 14it [00:02, 4.74it/s] 15it [00:03, 4.74it/s] 16it [00:03, 4.73it/s] 17it [00:03, 4.72it/s] 18it [00:03, 4.72it/s] 19it [00:04, 4.73it/s] 20it [00:04, 4.73it/s] 21it [00:04, 4.73it/s] 22it [00:04, 4.74it/s] 23it [00:04, 4.74it/s] 24it [00:05, 4.74it/s] 25it [00:05, 4.74it/s] 26it [00:05, 4.74it/s] 27it [00:05, 4.73it/s] 28it [00:05, 4.73it/s] 28it [00:05, 4.74it/s] Total safe images: 4 out of 4
Version Details
- Version ID
ad85b695d482244d0145db5e2c8e78852ecf608974bc9fd32cc19558e7a0f326
- Version Created
- January 28, 2025