joezboom/yossiimages 🖼️🔢❓📝✓ → 🖼️
Performance
48.9sTypical run time
161Total runs
About
Example Output
Prompt:
"a professional headshot of Yossi during a business photoshoot, with him facing the camera directly. His expression is calm and approachable, with a slight, confident smile that conveys warmth and professionalism. The lighting is soft, highlighting the contours of his face and giving a gentle shine to his eyes, creating a polished and high-quality look. He is dressed in a good looking t-shirt, with the background blurred subtly, focusing all attention on him. The overall tone is sleek and modern, with a subtle sense of authority and trustworthiness"
Output
Performance Metrics
48.88s
Prediction Time
48.89s
Total Time
All Input Parameters
{
"model": "dev",
"prompt": "a professional headshot of Yossi during a business photoshoot, with him facing the camera directly. His expression is calm and approachable, with a slight, confident smile that conveys warmth and professionalism. The lighting is soft, highlighting the contours of his face and giving a gentle shine to his eyes, creating a polished and high-quality look. He is dressed in a good looking t-shirt, with the background blurred subtly, focusing all attention on him. The overall tone is sleek and modern, with a subtle sense of authority and trustworthiness",
"lora_scale": 1,
"num_outputs": 4,
"aspect_ratio": "16:9",
"output_format": "webp",
"guidance_scale": 3.01,
"output_quality": 90,
"prompt_strength": 0.9,
"extra_lora_scale": 1,
"num_inference_steps": 30
}
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: 54730 Prompt: a professional headshot of Yossi during a business photoshoot, with him facing the camera directly. His expression is calm and approachable, with a slight, confident smile that conveys warmth and professionalism. The lighting is soft, highlighting the contours of his face and giving a gentle shine to his eyes, creating a polished and high-quality look. He is dressed in a good looking t-shirt, with the background blurred subtly, focusing all attention on him. The overall tone is sleek and modern, with a subtle sense of authority and trustworthiness [!] txt2img mode Using dev model free=7148848906240 Downloading weights 2024-09-13T18:59:47Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpgky2bddm/weights url=https://replicate.delivery/yhqm/YKECn8NW0v7jKJlF10sxkmlHsOgfgn0fcbkwhrWUzcpVFhcTA/trained_model.tar 2024-09-13T18:59:51Z | INFO | [ Complete ] dest=/tmp/tmpgky2bddm/weights size="172 MB" total_elapsed=3.604s url=https://replicate.delivery/yhqm/YKECn8NW0v7jKJlF10sxkmlHsOgfgn0fcbkwhrWUzcpVFhcTA/trained_model.tar Downloaded weights in 3.64s Loaded LoRAs in 16.88s 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:01<00:29, 1.03s/it] 7%|▋ | 2/30 [00:01<00:25, 1.09it/s] 10%|█ | 3/30 [00:02<00:26, 1.03it/s] 13%|█▎ | 4/30 [00:03<00:25, 1.01it/s] 17%|█▋ | 5/30 [00:04<00:25, 1.01s/it] 20%|██ | 6/30 [00:05<00:24, 1.02s/it] 23%|██▎ | 7/30 [00:07<00:23, 1.02s/it] 27%|██▋ | 8/30 [00:08<00:22, 1.02s/it] 30%|███ | 9/30 [00:09<00:21, 1.03s/it] 33%|███▎ | 10/30 [00:10<00:20, 1.03s/it] 37%|███▋ | 11/30 [00:11<00:19, 1.03s/it] 40%|████ | 12/30 [00:12<00:18, 1.03s/it] 43%|████▎ | 13/30 [00:13<00:17, 1.03s/it] 47%|████▋ | 14/30 [00:14<00:16, 1.03s/it] 50%|█████ | 15/30 [00:15<00:15, 1.03s/it] 53%|█████▎ | 16/30 [00:16<00:14, 1.03s/it] 57%|█████▋ | 17/30 [00:17<00:13, 1.03s/it] 60%|██████ | 18/30 [00:18<00:12, 1.03s/it] 63%|██████▎ | 19/30 [00:19<00:11, 1.03s/it] 67%|██████▋ | 20/30 [00:20<00:10, 1.03s/it] 70%|███████ | 21/30 [00:21<00:09, 1.03s/it] 73%|███████▎ | 22/30 [00:22<00:08, 1.04s/it] 77%|███████▋ | 23/30 [00:23<00:07, 1.03s/it] 80%|████████ | 24/30 [00:24<00:06, 1.03s/it] 83%|████████▎ | 25/30 [00:25<00:05, 1.03s/it] 87%|████████▋ | 26/30 [00:26<00:04, 1.03s/it] 90%|█████████ | 27/30 [00:27<00:03, 1.03s/it] 93%|█████████▎| 28/30 [00:28<00:02, 1.03s/it] 97%|█████████▋| 29/30 [00:29<00:01, 1.04s/it] 100%|██████████| 30/30 [00:30<00:00, 1.03s/it] 100%|██████████| 30/30 [00:30<00:00, 1.03s/it]
Version Details
- Version ID
1662cb698269a554d2cc142a33ba220f9181c3a9286c771b019f026529fd170b- Version Created
- September 13, 2024