marinasmile333/my-avatar-lora 🖼️🔢❓📝✓ → 🖼️
Performance
28.0sTypical run time
197Total runs
About
Example Output
Prompt:
"Warm, cinematic portrait of myavatar honey blonde gorgeous woman with perfect turquoise eyes sitting comfortably on a plush sofa in a cozy, tastefully decorated living room, surrounded by soft, diffused light from a nearby fireplace. [Your LoRA Avatar] is looking gently towards an empty space next to them, with a warm, inviting smile, as if expecting or acknowledging a loved one's presence. There are subtle details like a half-drunk cup of tea and an open book on a coffee table"
Output



Performance Metrics
27.98s
Prediction Time
28.01s
Total Time
All Input Parameters
{
"model": "dev",
"width": 1087,
"height": 1440,
"prompt": "Warm, cinematic portrait of myavatar honey blonde gorgeous woman with perfect turquoise eyes sitting comfortably on a plush sofa in a cozy, tastefully decorated living room, surrounded by soft, diffused light from a nearby fireplace. [Your LoRA Avatar] is looking gently towards an empty space next to them, with a warm, inviting smile, as if expecting or acknowledging a loved one's presence. There are subtle details like a half-drunk cup of tea and an open book on a coffee table",
"go_fast": false,
"lora_scale": 1.2,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "16:9",
"output_format": "jpg",
"guidance_scale": 10,
"output_quality": 80,
"prompt_strength": 0.4,
"extra_lora_scale": 0.5,
"num_inference_steps": 25
}
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
free=26874440036352 Downloading weights 2025-10-21T00:25:48Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpnghoq_m0/weights url=https://replicate.delivery/xezq/NaWKmjQdDdbEG1UHqGedxuy0b4l0SrexQ7xwzZdaylwFnTgVA/trained_model.tar 2025-10-21T00:25:48Z | INFO | [ Cache Service ] enabled=true scheme=http target=hermes.services.svc.cluster.local 2025-10-21T00:25:48Z | INFO | [ Cache URL Rewrite ] enabled=true target_url=http://hermes.services.svc.cluster.local/replicate.delivery/xezq/NaWKmjQdDdbEG1UHqGedxuy0b4l0SrexQ7xwzZdaylwFnTgVA/trained_model.tar url=https://replicate.delivery/xezq/NaWKmjQdDdbEG1UHqGedxuy0b4l0SrexQ7xwzZdaylwFnTgVA/trained_model.tar 2025-10-21T00:25:48Z | INFO | [ Redirect ] redirect_url=http://r8-east4-loras-ric1.cwlota.com/625c2bb558d4745846d9cb638eb355567112994fc7c137e822e6964228087b80?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Checksum-Mode=ENABLED&X-Amz-Credential=CWNZUVKLDHXVHEZN%2F20251021%2FUS-EAST-04A%2Fs3%2Faws4_request&X-Amz-Date=20251021T002548Z&X-Amz-Expires=600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=43a7d9057edd4f42eefbf6fa17860581a73bae343d78bcdac28d956f4631b273 url=http://hermes.services.svc.cluster.local/replicate.delivery/xezq/NaWKmjQdDdbEG1UHqGedxuy0b4l0SrexQ7xwzZdaylwFnTgVA/trained_model.tar 2025-10-21T00:25:49Z | INFO | [ Complete ] dest=/tmp/tmpnghoq_m0/weights size="172 MB" total_elapsed=0.313s url=https://replicate.delivery/xezq/NaWKmjQdDdbEG1UHqGedxuy0b4l0SrexQ7xwzZdaylwFnTgVA/trained_model.tar Downloaded weights in 0.38s Loaded LoRAs in 0.94s Using seed: 24079 Prompt: Warm, cinematic portrait of myavatar honey blonde gorgeous woman with perfect turquoise eyes sitting comfortably on a plush sofa in a cozy, tastefully decorated living room, surrounded by soft, diffused light from a nearby fireplace. [Your LoRA Avatar] is looking gently towards an empty space next to them, with a warm, inviting smile, as if expecting or acknowledging a loved one's presence. There are subtle details like a half-drunk cup of tea and an open book on a coffee table [!] txt2img mode 0%| | 0/25 [00:00<?, ?it/s] 4%|▍ | 1/25 [00:00<00:23, 1.04it/s] 8%|▊ | 2/25 [00:01<00:19, 1.16it/s] 12%|█▏ | 3/25 [00:02<00:19, 1.10it/s] 16%|█▌ | 4/25 [00:03<00:19, 1.08it/s] 20%|██ | 5/25 [00:04<00:18, 1.06it/s] 24%|██▍ | 6/25 [00:05<00:18, 1.05it/s] 28%|██▊ | 7/25 [00:06<00:17, 1.05it/s] 32%|███▏ | 8/25 [00:07<00:16, 1.04it/s] 36%|███▌ | 9/25 [00:08<00:15, 1.04it/s] 40%|████ | 10/25 [00:09<00:14, 1.04it/s] 44%|████▍ | 11/25 [00:10<00:13, 1.04it/s] 48%|████▊ | 12/25 [00:11<00:12, 1.04it/s] 52%|█████▏ | 13/25 [00:12<00:11, 1.04it/s] 56%|█████▌ | 14/25 [00:13<00:10, 1.04it/s] 60%|██████ | 15/25 [00:14<00:09, 1.04it/s] 64%|██████▍ | 16/25 [00:15<00:08, 1.04it/s] 68%|██████▊ | 17/25 [00:16<00:07, 1.04it/s] 72%|███████▏ | 18/25 [00:17<00:06, 1.04it/s] 76%|███████▌ | 19/25 [00:18<00:05, 1.04it/s] 80%|████████ | 20/25 [00:19<00:04, 1.03it/s] 84%|████████▍ | 21/25 [00:20<00:03, 1.04it/s] 88%|████████▊ | 22/25 [00:21<00:02, 1.04it/s] 92%|█████████▏| 23/25 [00:22<00:01, 1.04it/s] 96%|█████████▌| 24/25 [00:22<00:00, 1.04it/s] 100%|██████████| 25/25 [00:23<00:00, 1.04it/s] 100%|██████████| 25/25 [00:23<00:00, 1.04it/s] Total safe images: 4 out of 4
Version Details
- Version ID
f6a3829d41782050d35c2539a72aa91bfa0c6eb55d92af9019df50aaaf7cf585- Version Created
- October 18, 2025