drrhinoai / aisonya
- Public
- 71 runs
-
H100
Prediction
drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28aIDhtazakc7esrme0cm56v88t745gStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- AISONYA, an elite swimwear model, is standing at the rail of a yacht, admiring the panoramic view of the blue-green ocean. The neon accents of her swimsuit perfectly compliment her hair and eyes. The ocean breeze blows gently through her hair. Her fingers rest gently on the teak wood as she leans against the rail.
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing at the rail of a yacht, admiring the panoramic view of the blue-green ocean. The neon accents of her swimsuit perfectly compliment her hair and eyes. The ocean breeze blows gently through her hair. Her fingers rest gently on the teak wood as she leans against the rail.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", { input: { model: "dev", prompt: "AISONYA, an elite swimwear model, is standing at the rail of a yacht, admiring the panoramic view of the blue-green ocean. The neon accents of her swimsuit perfectly compliment her hair and eyes. The ocean breeze blows gently through her hair. Her fingers rest gently on the teak wood as she leans against the rail.", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", input={ "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing at the rail of a yacht, admiring the panoramic view of the blue-green ocean. The neon accents of her swimsuit perfectly compliment her hair and eyes. The ocean breeze blows gently through her hair. Her fingers rest gently on the teak wood as she leans against the rail.", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", "input": { "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing at the rail of a yacht, admiring the panoramic view of the blue-green ocean. The neon accents of her swimsuit perfectly compliment her hair and eyes. The ocean breeze blows gently through her hair. Her fingers rest gently on the teak wood as she leans against the rail.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/drrhinoai/aisonya@sha256:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a \ -i 'model="dev"' \ -i 'prompt="AISONYA, an elite swimwear model, is standing at the rail of a yacht, admiring the panoramic view of the blue-green ocean. The neon accents of her swimsuit perfectly compliment her hair and eyes. The ocean breeze blows gently through her hair. Her fingers rest gently on the teak wood as she leans against the rail."' \ -i 'go_fast=false' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="webp"' \ -i 'guidance_scale=3' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=28'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/drrhinoai/aisonya@sha256:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing at the rail of a yacht, admiring the panoramic view of the blue-green ocean. The neon accents of her swimsuit perfectly compliment her hair and eyes. The ocean breeze blows gently through her hair. Her fingers rest gently on the teak wood as she leans against the rail.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2025-01-03T01:10:24.372722Z", "created_at": "2025-01-03T01:10:15.670000Z", "data_removed": false, "error": null, "id": "htazakc7esrme0cm56v88t745g", "input": { "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing at the rail of a yacht, admiring the panoramic view of the blue-green ocean. The neon accents of her swimsuit perfectly compliment her hair and eyes. The ocean breeze blows gently through her hair. Her fingers rest gently on the teak wood as she leans against the rail.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-01-03 01:10:15.734 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-03 01:10:15.735 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 93%|█████████▎| 283/304 [00:00<00:00, 2815.56it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2702.62it/s]\n2025-01-03 01:10:15.847 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\nfree=29483755671552\nDownloading weights\n2025-01-03T01:10:15Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmptdclb8oa/weights url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar\n2025-01-03T01:10:17Z | INFO | [ Complete ] dest=/tmp/tmptdclb8oa/weights size=\"172 MB\" total_elapsed=1.996s url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar\nDownloaded weights in 2.02s\n2025-01-03 01:10:17.869 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/85bfb74a0d20402c\n2025-01-03 01:10:17.940 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-03 01:10:17.940 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-03 01:10:17.941 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 93%|█████████▎| 283/304 [00:00<00:00, 2821.41it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2707.67it/s]\n2025-01-03 01:10:18.053 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s\nUsing seed: 3762\n0it [00:00, ?it/s]\n1it [00:00, 8.30it/s]\n2it [00:00, 5.77it/s]\n3it [00:00, 5.25it/s]\n4it [00:00, 5.04it/s]\n5it [00:00, 4.88it/s]\n6it [00:01, 4.80it/s]\n7it [00:01, 4.77it/s]\n8it [00:01, 4.76it/s]\n9it [00:01, 4.75it/s]\n10it [00:02, 4.73it/s]\n11it [00:02, 4.70it/s]\n12it [00:02, 4.71it/s]\n13it [00:02, 4.71it/s]\n14it [00:02, 4.70it/s]\n15it [00:03, 4.69it/s]\n16it [00:03, 4.69it/s]\n17it [00:03, 4.70it/s]\n18it [00:03, 4.70it/s]\n19it [00:03, 4.68it/s]\n20it [00:04, 4.68it/s]\n21it [00:04, 4.67it/s]\n22it [00:04, 4.67it/s]\n23it [00:04, 4.67it/s]\n24it [00:05, 4.67it/s]\n25it [00:05, 4.67it/s]\n26it [00:05, 4.68it/s]\n27it [00:05, 4.68it/s]\n28it [00:05, 4.70it/s]\n28it [00:05, 4.77it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 8.637159889, "total_time": 8.702722 }, "output": [ "https://replicate.delivery/xezq/H47XAwBEHUJVFNzIItGgi98XOT7g5gM0I7PlDX0Ev7AArTAF/out-0.webp" ], "started_at": "2025-01-03T01:10:15.735562Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-mgm4klwjsbgw3kbzf7o623tioorhrf55lf6z6vowvysnczfkbg3a", "get": "https://api.replicate.com/v1/predictions/htazakc7esrme0cm56v88t745g", "cancel": "https://api.replicate.com/v1/predictions/htazakc7esrme0cm56v88t745g/cancel" }, "version": "2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a" }
Generated in2025-01-03 01:10:15.734 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-03 01:10:15.735 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 93%|█████████▎| 283/304 [00:00<00:00, 2815.56it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2702.62it/s] 2025-01-03 01:10:15.847 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s free=29483755671552 Downloading weights 2025-01-03T01:10:15Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmptdclb8oa/weights url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar 2025-01-03T01:10:17Z | INFO | [ Complete ] dest=/tmp/tmptdclb8oa/weights size="172 MB" total_elapsed=1.996s url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar Downloaded weights in 2.02s 2025-01-03 01:10:17.869 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/85bfb74a0d20402c 2025-01-03 01:10:17.940 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-03 01:10:17.940 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-03 01:10:17.941 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 93%|█████████▎| 283/304 [00:00<00:00, 2821.41it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2707.67it/s] 2025-01-03 01:10:18.053 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s Using seed: 3762 0it [00:00, ?it/s] 1it [00:00, 8.30it/s] 2it [00:00, 5.77it/s] 3it [00:00, 5.25it/s] 4it [00:00, 5.04it/s] 5it [00:00, 4.88it/s] 6it [00:01, 4.80it/s] 7it [00:01, 4.77it/s] 8it [00:01, 4.76it/s] 9it [00:01, 4.75it/s] 10it [00:02, 4.73it/s] 11it [00:02, 4.70it/s] 12it [00:02, 4.71it/s] 13it [00:02, 4.71it/s] 14it [00:02, 4.70it/s] 15it [00:03, 4.69it/s] 16it [00:03, 4.69it/s] 17it [00:03, 4.70it/s] 18it [00:03, 4.70it/s] 19it [00:03, 4.68it/s] 20it [00:04, 4.68it/s] 21it [00:04, 4.67it/s] 22it [00:04, 4.67it/s] 23it [00:04, 4.67it/s] 24it [00:05, 4.67it/s] 25it [00:05, 4.67it/s] 26it [00:05, 4.68it/s] 27it [00:05, 4.68it/s] 28it [00:05, 4.70it/s] 28it [00:05, 4.77it/s] Total safe images: 1 out of 1
Prediction
drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28aIDvcyfrwa609rm80cm56vtqxemk4StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- AISONYA, an elite swimwear model, is standing at the rail of a yacht, admiring the panoramic view of the blue-green ocean. The neon accents of her swimsuit perfectly compliment her hair and eyes. The ocean breeze blows gently through her hair. Her fingers rest gently on the teak wood as she leans against the rail.
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing at the rail of a yacht, admiring the panoramic view of the blue-green ocean. The neon accents of her swimsuit perfectly compliment her hair and eyes. The ocean breeze blows gently through her hair. Her fingers rest gently on the teak wood as she leans against the rail.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", { input: { model: "dev", prompt: "AISONYA, an elite swimwear model, is standing at the rail of a yacht, admiring the panoramic view of the blue-green ocean. The neon accents of her swimsuit perfectly compliment her hair and eyes. The ocean breeze blows gently through her hair. Her fingers rest gently on the teak wood as she leans against the rail.", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", input={ "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing at the rail of a yacht, admiring the panoramic view of the blue-green ocean. The neon accents of her swimsuit perfectly compliment her hair and eyes. The ocean breeze blows gently through her hair. Her fingers rest gently on the teak wood as she leans against the rail.", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", "input": { "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing at the rail of a yacht, admiring the panoramic view of the blue-green ocean. The neon accents of her swimsuit perfectly compliment her hair and eyes. The ocean breeze blows gently through her hair. Her fingers rest gently on the teak wood as she leans against the rail.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/drrhinoai/aisonya@sha256:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a \ -i 'model="dev"' \ -i 'prompt="AISONYA, an elite swimwear model, is standing at the rail of a yacht, admiring the panoramic view of the blue-green ocean. The neon accents of her swimsuit perfectly compliment her hair and eyes. The ocean breeze blows gently through her hair. Her fingers rest gently on the teak wood as she leans against the rail."' \ -i 'go_fast=false' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="webp"' \ -i 'guidance_scale=3' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=28'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/drrhinoai/aisonya@sha256:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing at the rail of a yacht, admiring the panoramic view of the blue-green ocean. The neon accents of her swimsuit perfectly compliment her hair and eyes. The ocean breeze blows gently through her hair. Her fingers rest gently on the teak wood as she leans against the rail.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2025-01-03T01:11:14.786025Z", "created_at": "2025-01-03T01:11:04.450000Z", "data_removed": false, "error": null, "id": "vcyfrwa609rm80cm56vtqxemk4", "input": { "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing at the rail of a yacht, admiring the panoramic view of the blue-green ocean. The neon accents of her swimsuit perfectly compliment her hair and eyes. The ocean breeze blows gently through her hair. Her fingers rest gently on the teak wood as she leans against the rail.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-01-03 01:11:04.476 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-03 01:11:04.477 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 92%|█████████▏| 281/304 [00:00<00:00, 2807.95it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2614.81it/s]\n2025-01-03 01:11:04.594 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s\nfree=29533907488768\nDownloading weights\n2025-01-03T01:11:04Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpc4s_nxbd/weights url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar\n2025-01-03T01:11:08Z | INFO | [ Complete ] dest=/tmp/tmpc4s_nxbd/weights size=\"172 MB\" total_elapsed=3.898s url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar\nDownloaded weights in 3.92s\n2025-01-03 01:11:08.519 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/85bfb74a0d20402c\n2025-01-03 01:11:08.589 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-03 01:11:08.589 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-03 01:11:08.589 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 93%|█████████▎| 283/304 [00:00<00:00, 2826.62it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2620.59it/s]\n2025-01-03 01:11:08.706 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s\nUsing seed: 9116\n0it [00:00, ?it/s]\n1it [00:00, 8.38it/s]\n2it [00:00, 5.88it/s]\n3it [00:00, 5.36it/s]\n4it [00:00, 5.15it/s]\n5it [00:00, 5.03it/s]\n6it [00:01, 4.93it/s]\n7it [00:01, 4.90it/s]\n8it [00:01, 4.88it/s]\n9it [00:01, 4.87it/s]\n10it [00:01, 4.85it/s]\n11it [00:02, 4.84it/s]\n12it [00:02, 4.83it/s]\n13it [00:02, 4.83it/s]\n14it [00:02, 4.83it/s]\n15it [00:03, 4.83it/s]\n16it [00:03, 4.82it/s]\n17it [00:03, 4.82it/s]\n18it [00:03, 4.81it/s]\n19it [00:03, 4.81it/s]\n20it [00:04, 4.81it/s]\n21it [00:04, 4.81it/s]\n22it [00:04, 4.80it/s]\n23it [00:04, 4.80it/s]\n24it [00:04, 4.81it/s]\n25it [00:05, 4.81it/s]\n26it [00:05, 4.81it/s]\n27it [00:05, 4.81it/s]\n28it [00:05, 4.81it/s]\n28it [00:05, 4.89it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 10.308198695, "total_time": 10.336025 }, "output": [ "https://replicate.delivery/xezq/VCdsB2tTGTpYFF14CCWqMUNAosJJZAEqVtidKW1un4sMrTAF/out-0.webp" ], "started_at": "2025-01-03T01:11:04.477826Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-vbeeibpfi5sputarkynfhraoh5aadkmunprw62xntoaejqdj2drq", "get": "https://api.replicate.com/v1/predictions/vcyfrwa609rm80cm56vtqxemk4", "cancel": "https://api.replicate.com/v1/predictions/vcyfrwa609rm80cm56vtqxemk4/cancel" }, "version": "2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a" }
Generated in2025-01-03 01:11:04.476 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-03 01:11:04.477 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 92%|█████████▏| 281/304 [00:00<00:00, 2807.95it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2614.81it/s] 2025-01-03 01:11:04.594 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s free=29533907488768 Downloading weights 2025-01-03T01:11:04Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpc4s_nxbd/weights url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar 2025-01-03T01:11:08Z | INFO | [ Complete ] dest=/tmp/tmpc4s_nxbd/weights size="172 MB" total_elapsed=3.898s url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar Downloaded weights in 3.92s 2025-01-03 01:11:08.519 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/85bfb74a0d20402c 2025-01-03 01:11:08.589 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-03 01:11:08.589 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-03 01:11:08.589 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 93%|█████████▎| 283/304 [00:00<00:00, 2826.62it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2620.59it/s] 2025-01-03 01:11:08.706 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s Using seed: 9116 0it [00:00, ?it/s] 1it [00:00, 8.38it/s] 2it [00:00, 5.88it/s] 3it [00:00, 5.36it/s] 4it [00:00, 5.15it/s] 5it [00:00, 5.03it/s] 6it [00:01, 4.93it/s] 7it [00:01, 4.90it/s] 8it [00:01, 4.88it/s] 9it [00:01, 4.87it/s] 10it [00:01, 4.85it/s] 11it [00:02, 4.84it/s] 12it [00:02, 4.83it/s] 13it [00:02, 4.83it/s] 14it [00:02, 4.83it/s] 15it [00:03, 4.83it/s] 16it [00:03, 4.82it/s] 17it [00:03, 4.82it/s] 18it [00:03, 4.81it/s] 19it [00:03, 4.81it/s] 20it [00:04, 4.81it/s] 21it [00:04, 4.81it/s] 22it [00:04, 4.80it/s] 23it [00:04, 4.80it/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, 4.81it/s] 28it [00:05, 4.89it/s] Total safe images: 1 out of 1
Prediction
drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28aID5rdv026t4drme0cm56wrc703x4StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- AISONYA, an elite swimwear model, is standing on stage with other finalists, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing on stage with other finalists, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", { input: { model: "dev", prompt: "AISONYA, an elite swimwear model, is standing on stage with other finalists, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", input={ "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing on stage with other finalists, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", "input": { "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing on stage with other finalists, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/drrhinoai/aisonya@sha256:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a \ -i 'model="dev"' \ -i 'prompt="AISONYA, an elite swimwear model, is standing on stage with other finalists, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them."' \ -i 'go_fast=false' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="webp"' \ -i 'guidance_scale=3' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=28'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/drrhinoai/aisonya@sha256:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing on stage with other finalists, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2025-01-03T01:14:03.003698Z", "created_at": "2025-01-03T01:13:53.443000Z", "data_removed": false, "error": null, "id": "5rdv026t4drme0cm56wrc703x4", "input": { "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing on stage with other finalists, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-01-03 01:13:53.757 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-03 01:13:53.758 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 92%|█████████▏| 280/304 [00:00<00:00, 2784.36it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2723.53it/s]\n2025-01-03 01:13:53.870 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\nfree=28828882669568\nDownloading weights\n2025-01-03T01:13:53Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmppkpzrsvb/weights url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar\n2025-01-03T01:13:56Z | INFO | [ Complete ] dest=/tmp/tmppkpzrsvb/weights size=\"172 MB\" total_elapsed=2.746s url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar\nDownloaded weights in 2.77s\n2025-01-03 01:13:56.643 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/85bfb74a0d20402c\n2025-01-03 01:13:56.715 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-03 01:13:56.715 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-03 01:13:56.716 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 92%|█████████▏| 280/304 [00:00<00:00, 2786.67it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2726.17it/s]\n2025-01-03 01:13:56.828 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s\nUsing seed: 27684\n0it [00:00, ?it/s]\n1it [00:00, 8.34it/s]\n2it [00:00, 5.82it/s]\n3it [00:00, 5.31it/s]\n4it [00:00, 5.09it/s]\n5it [00:00, 4.92it/s]\n6it [00:01, 4.85it/s]\n7it [00:01, 4.82it/s]\n8it [00:01, 4.81it/s]\n9it [00:01, 4.80it/s]\n10it [00:02, 4.77it/s]\n11it [00:02, 4.75it/s]\n12it [00:02, 4.75it/s]\n13it [00:02, 4.75it/s]\n14it [00:02, 4.75it/s]\n15it [00:03, 4.74it/s]\n16it [00:03, 4.73it/s]\n17it [00:03, 4.74it/s]\n18it [00:03, 4.74it/s]\n19it [00:03, 4.74it/s]\n20it [00:04, 4.74it/s]\n21it [00:04, 4.73it/s]\n22it [00:04, 4.74it/s]\n23it [00:04, 4.75it/s]\n24it [00:04, 4.75it/s]\n25it [00:05, 4.75it/s]\n26it [00:05, 4.75it/s]\n27it [00:05, 4.74it/s]\n28it [00:05, 4.75it/s]\n28it [00:05, 4.82it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 9.245497843, "total_time": 9.560698 }, "output": [ "https://replicate.delivery/xezq/adhnLkYvr1KFEpmUE3huODKsH54fUAliYmUpkUv1w98tXnAKA/out-0.webp" ], "started_at": "2025-01-03T01:13:53.758200Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-adrjyhhbp3ycfqjc4byjfewn7rqicllazbbhvxgozxbpz3i2cwxa", "get": "https://api.replicate.com/v1/predictions/5rdv026t4drme0cm56wrc703x4", "cancel": "https://api.replicate.com/v1/predictions/5rdv026t4drme0cm56wrc703x4/cancel" }, "version": "2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a" }
Generated in2025-01-03 01:13:53.757 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-03 01:13:53.758 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 92%|█████████▏| 280/304 [00:00<00:00, 2784.36it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2723.53it/s] 2025-01-03 01:13:53.870 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s free=28828882669568 Downloading weights 2025-01-03T01:13:53Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmppkpzrsvb/weights url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar 2025-01-03T01:13:56Z | INFO | [ Complete ] dest=/tmp/tmppkpzrsvb/weights size="172 MB" total_elapsed=2.746s url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar Downloaded weights in 2.77s 2025-01-03 01:13:56.643 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/85bfb74a0d20402c 2025-01-03 01:13:56.715 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-03 01:13:56.715 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-03 01:13:56.716 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 92%|█████████▏| 280/304 [00:00<00:00, 2786.67it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2726.17it/s] 2025-01-03 01:13:56.828 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s Using seed: 27684 0it [00:00, ?it/s] 1it [00:00, 8.34it/s] 2it [00:00, 5.82it/s] 3it [00:00, 5.31it/s] 4it [00:00, 5.09it/s] 5it [00:00, 4.92it/s] 6it [00:01, 4.85it/s] 7it [00:01, 4.82it/s] 8it [00:01, 4.81it/s] 9it [00:01, 4.80it/s] 10it [00:02, 4.77it/s] 11it [00:02, 4.75it/s] 12it [00:02, 4.75it/s] 13it [00:02, 4.75it/s] 14it [00:02, 4.75it/s] 15it [00:03, 4.74it/s] 16it [00:03, 4.73it/s] 17it [00:03, 4.74it/s] 18it [00:03, 4.74it/s] 19it [00:03, 4.74it/s] 20it [00:04, 4.74it/s] 21it [00:04, 4.73it/s] 22it [00:04, 4.74it/s] 23it [00:04, 4.75it/s] 24it [00:04, 4.75it/s] 25it [00:05, 4.75it/s] 26it [00:05, 4.75it/s] 27it [00:05, 4.74it/s] 28it [00:05, 4.75it/s] 28it [00:05, 4.82it/s] Total safe images: 1 out of 1
Prediction
drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28aID80j9ggzp39rmc0cm56xsm553f4StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- AISONYA, an elite swimwear model, is standing on stage with other finalists, showing the backs of their swimsuits for the final showdown, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing on stage with other finalists, showing the backs of their swimsuits for the final showdown, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", { input: { model: "dev", prompt: "AISONYA, an elite swimwear model, is standing on stage with other finalists, showing the backs of their swimsuits for the final showdown, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", input={ "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing on stage with other finalists, showing the backs of their swimsuits for the final showdown, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", "input": { "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing on stage with other finalists, showing the backs of their swimsuits for the final showdown, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/drrhinoai/aisonya@sha256:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a \ -i 'model="dev"' \ -i 'prompt="AISONYA, an elite swimwear model, is standing on stage with other finalists, showing the backs of their swimsuits for the final showdown, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them."' \ -i 'go_fast=false' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="webp"' \ -i 'guidance_scale=3' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=28'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/drrhinoai/aisonya@sha256:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing on stage with other finalists, showing the backs of their swimsuits for the final showdown, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2025-01-03T01:16:20.428227Z", "created_at": "2025-01-03T01:16:11.674000Z", "data_removed": false, "error": null, "id": "80j9ggzp39rmc0cm56xsm553f4", "input": { "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing on stage with other finalists, showing the backs of their swimsuits for the final showdown, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-01-03 01:16:12.183 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-03 01:16:12.183 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 89%|████████▉ | 271/304 [00:00<00:00, 2684.74it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2608.28it/s]\n2025-01-03 01:16:12.300 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s\nfree=28532446265344\nDownloading weights\n2025-01-03T01:16:12Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmptglmmufy/weights url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar\n2025-01-03T01:16:14Z | INFO | [ Complete ] dest=/tmp/tmptglmmufy/weights size=\"172 MB\" total_elapsed=1.823s url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar\nDownloaded weights in 1.85s\n2025-01-03 01:16:14.149 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/85bfb74a0d20402c\n2025-01-03 01:16:14.220 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-03 01:16:14.220 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-03 01:16:14.220 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 89%|████████▉ | 271/304 [00:00<00:00, 2686.20it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2609.10it/s]\n2025-01-03 01:16:14.337 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s\nUsing seed: 16657\n0it [00:00, ?it/s]\n1it [00:00, 8.42it/s]\n2it [00:00, 5.86it/s]\n3it [00:00, 5.36it/s]\n4it [00:00, 5.15it/s]\n5it [00:00, 5.00it/s]\n6it [00:01, 4.91it/s]\n7it [00:01, 4.89it/s]\n8it [00:01, 4.87it/s]\n9it [00:01, 4.85it/s]\n10it [00:01, 4.83it/s]\n11it [00:02, 4.82it/s]\n12it [00:02, 4.82it/s]\n13it [00:02, 4.82it/s]\n14it [00:02, 4.82it/s]\n15it [00:03, 4.82it/s]\n16it [00:03, 4.82it/s]\n17it [00:03, 4.81it/s]\n18it [00:03, 4.82it/s]\n19it [00:03, 4.82it/s]\n20it [00:04, 4.80it/s]\n21it [00:04, 4.80it/s]\n22it [00:04, 4.80it/s]\n23it [00:04, 4.81it/s]\n24it [00:04, 4.82it/s]\n25it [00:05, 4.81it/s]\n26it [00:05, 4.81it/s]\n27it [00:05, 4.81it/s]\n28it [00:05, 4.81it/s]\n28it [00:05, 4.89it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 8.243784036, "total_time": 8.754227 }, "output": [ "https://replicate.delivery/xezq/Bnc0zwV7NxJEHZJxebxgberrTRdz11dCKraLmpoJs4akxOBUA/out-0.webp" ], "started_at": "2025-01-03T01:16:12.184443Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-o2ydqb33q6w5opybbflt5u62afb4cbpji6w2p6edjidylkmhsbaa", "get": "https://api.replicate.com/v1/predictions/80j9ggzp39rmc0cm56xsm553f4", "cancel": "https://api.replicate.com/v1/predictions/80j9ggzp39rmc0cm56xsm553f4/cancel" }, "version": "2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a" }
Generated in2025-01-03 01:16:12.183 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-03 01:16:12.183 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 89%|████████▉ | 271/304 [00:00<00:00, 2684.74it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2608.28it/s] 2025-01-03 01:16:12.300 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s free=28532446265344 Downloading weights 2025-01-03T01:16:12Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmptglmmufy/weights url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar 2025-01-03T01:16:14Z | INFO | [ Complete ] dest=/tmp/tmptglmmufy/weights size="172 MB" total_elapsed=1.823s url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar Downloaded weights in 1.85s 2025-01-03 01:16:14.149 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/85bfb74a0d20402c 2025-01-03 01:16:14.220 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-03 01:16:14.220 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-03 01:16:14.220 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 89%|████████▉ | 271/304 [00:00<00:00, 2686.20it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2609.10it/s] 2025-01-03 01:16:14.337 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s Using seed: 16657 0it [00:00, ?it/s] 1it [00:00, 8.42it/s] 2it [00:00, 5.86it/s] 3it [00:00, 5.36it/s] 4it [00:00, 5.15it/s] 5it [00:00, 5.00it/s] 6it [00:01, 4.91it/s] 7it [00:01, 4.89it/s] 8it [00:01, 4.87it/s] 9it [00:01, 4.85it/s] 10it [00:01, 4.83it/s] 11it [00:02, 4.82it/s] 12it [00:02, 4.82it/s] 13it [00:02, 4.82it/s] 14it [00:02, 4.82it/s] 15it [00:03, 4.82it/s] 16it [00:03, 4.82it/s] 17it [00:03, 4.81it/s] 18it [00:03, 4.82it/s] 19it [00:03, 4.82it/s] 20it [00:04, 4.80it/s] 21it [00:04, 4.80it/s] 22it [00:04, 4.80it/s] 23it [00:04, 4.81it/s] 24it [00:04, 4.82it/s] 25it [00:05, 4.81it/s] 26it [00:05, 4.81it/s] 27it [00:05, 4.81it/s] 28it [00:05, 4.81it/s] 28it [00:05, 4.89it/s] Total safe images: 1 out of 1
Prediction
drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28aID53t1zm5va9rmc0cm56ybm8vangStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- AISONYA, an elite swimwear model, is standing on stage with other finalists, showing the backs of their swimsuits for the final showdown, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3
- output_quality
- 80
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing on stage with other finalists, showing the backs of their swimsuits for the final showdown, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", { input: { model: "dev", prompt: "AISONYA, an elite swimwear model, is standing on stage with other finalists, showing the backs of their swimsuits for the final showdown, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3, output_quality: 80, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", input={ "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing on stage with other finalists, showing the backs of their swimsuits for the final showdown, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", "input": { "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing on stage with other finalists, showing the backs of their swimsuits for the final showdown, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/drrhinoai/aisonya@sha256:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a \ -i 'model="dev"' \ -i 'prompt="AISONYA, an elite swimwear model, is standing on stage with other finalists, showing the backs of their swimsuits for the final showdown, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them."' \ -i 'go_fast=false' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="webp"' \ -i 'guidance_scale=3' \ -i 'output_quality=80' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=28'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/drrhinoai/aisonya@sha256:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing on stage with other finalists, showing the backs of their swimsuits for the final showdown, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2025-01-03T01:17:10.676986Z", "created_at": "2025-01-03T01:17:02.162000Z", "data_removed": false, "error": null, "id": "53t1zm5va9rmc0cm56ybm8vang", "input": { "model": "dev", "prompt": "AISONYA, an elite swimwear model, is standing on stage with other finalists, showing the backs of their swimsuits for the final showdown, awaiting the decision of the judges as to who the #1 swimwear model will be this year. The neon accents of her swimsuit perfectly compliment her hair and eyes. All of the contestants wear their happiest expressions as they await the decision. AISONYA knows she stands out as the best among them.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3, "output_quality": 80, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-01-03 01:17:02.201 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-03 01:17:02.201 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 91%|█████████▏| 278/304 [00:00<00:00, 2778.81it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2631.22it/s]\n2025-01-03 01:17:02.317 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s\nfree=29140292231168\nDownloading weights\n2025-01-03T01:17:02Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp4efaofwe/weights url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar\n2025-01-03T01:17:04Z | INFO | [ Complete ] dest=/tmp/tmp4efaofwe/weights size=\"172 MB\" total_elapsed=2.038s url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar\nDownloaded weights in 2.06s\n2025-01-03 01:17:04.380 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/85bfb74a0d20402c\n2025-01-03 01:17:04.448 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-03 01:17:04.449 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-03 01:17:04.449 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 92%|█████████▏| 279/304 [00:00<00:00, 2789.35it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2635.58it/s]\n2025-01-03 01:17:04.564 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s\nUsing seed: 54747\n0it [00:00, ?it/s]\n1it [00:00, 8.32it/s]\n2it [00:00, 5.83it/s]\n3it [00:00, 5.32it/s]\n4it [00:00, 5.11it/s]\n5it [00:00, 5.00it/s]\n6it [00:01, 4.92it/s]\n7it [00:01, 4.88it/s]\n8it [00:01, 4.85it/s]\n9it [00:01, 4.84it/s]\n10it [00:01, 4.83it/s]\n11it [00:02, 4.82it/s]\n12it [00:02, 4.81it/s]\n13it [00:02, 4.80it/s]\n14it [00:02, 4.80it/s]\n15it [00:03, 4.81it/s]\n16it [00:03, 4.80it/s]\n17it [00:03, 4.80it/s]\n18it [00:03, 4.79it/s]\n19it [00:03, 4.79it/s]\n20it [00:04, 4.79it/s]\n21it [00:04, 4.79it/s]\n22it [00:04, 4.80it/s]\n23it [00:04, 4.81it/s]\n24it [00:04, 4.81it/s]\n25it [00:05, 4.80it/s]\n26it [00:05, 4.80it/s]\n27it [00:05, 4.81it/s]\n28it [00:05, 4.81it/s]\n28it [00:05, 4.87it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 8.474678817, "total_time": 8.514986 }, "output": [ "https://replicate.delivery/xezq/xRnGpkxcSxIGF5nefwAbP7F6xgGng0BwPGCRWonUYahWyOBUA/out-0.webp" ], "started_at": "2025-01-03T01:17:02.202307Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-z6astx3o5vakkccxtd7l6ku26x5xvsetmt3hlz5c7vkzndpqfp2q", "get": "https://api.replicate.com/v1/predictions/53t1zm5va9rmc0cm56ybm8vang", "cancel": "https://api.replicate.com/v1/predictions/53t1zm5va9rmc0cm56ybm8vang/cancel" }, "version": "2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a" }
Generated in2025-01-03 01:17:02.201 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-03 01:17:02.201 | 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, 2778.81it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2631.22it/s] 2025-01-03 01:17:02.317 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s free=29140292231168 Downloading weights 2025-01-03T01:17:02Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp4efaofwe/weights url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar 2025-01-03T01:17:04Z | INFO | [ Complete ] dest=/tmp/tmp4efaofwe/weights size="172 MB" total_elapsed=2.038s url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar Downloaded weights in 2.06s 2025-01-03 01:17:04.380 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/85bfb74a0d20402c 2025-01-03 01:17:04.448 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-03 01:17:04.449 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-03 01:17:04.449 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 92%|█████████▏| 279/304 [00:00<00:00, 2789.35it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2635.58it/s] 2025-01-03 01:17:04.564 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s Using seed: 54747 0it [00:00, ?it/s] 1it [00:00, 8.32it/s] 2it [00:00, 5.83it/s] 3it [00:00, 5.32it/s] 4it [00:00, 5.11it/s] 5it [00:00, 5.00it/s] 6it [00:01, 4.92it/s] 7it [00:01, 4.88it/s] 8it [00:01, 4.85it/s] 9it [00:01, 4.84it/s] 10it [00:01, 4.83it/s] 11it [00:02, 4.82it/s] 12it [00:02, 4.81it/s] 13it [00:02, 4.80it/s] 14it [00:02, 4.80it/s] 15it [00:03, 4.81it/s] 16it [00:03, 4.80it/s] 17it [00:03, 4.80it/s] 18it [00:03, 4.79it/s] 19it [00:03, 4.79it/s] 20it [00:04, 4.79it/s] 21it [00:04, 4.79it/s] 22it [00:04, 4.80it/s] 23it [00:04, 4.81it/s] 24it [00:04, 4.81it/s] 25it [00:05, 4.80it/s] 26it [00:05, 4.80it/s] 27it [00:05, 4.81it/s] 28it [00:05, 4.81it/s] 28it [00:05, 4.87it/s] Total safe images: 1 out of 1
Prediction
drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28aID5dj9wt7rkxrme0cm6e3tykp7b8StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- AISONYA, a stunningly beautiful woman with honey-blonde hair, is Little Red Riding Hood. She is on a forest path, defiantly and fearlessly confronting a werewolf who wants to eat the food she has packed for her grandmother. She faces the fierce beast in a dynamic fighting stance, her bare legs spread wide for balance, bare muscular arms out, ready to strike. Her red cloak billows behind her as she moves in battle. The monstrous man-wolf has malevolent red eyes, its fangs slathered with drool, it's fearsome claws ready to rend and tear.
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- jpg
- guidance_scale
- 3
- output_quality
- 100
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "AISONYA, a stunningly beautiful woman with honey-blonde hair, is Little Red Riding Hood. She is on a forest path, defiantly and fearlessly confronting a werewolf who wants to eat the food she has packed for her grandmother. She faces the fierce beast in a dynamic fighting stance, her bare legs spread wide for balance, bare muscular arms out, ready to strike. Her red cloak billows behind her as she moves in battle. The monstrous man-wolf has malevolent red eyes, its fangs slathered with drool, it's fearsome claws ready to rend and tear.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", { input: { model: "dev", prompt: "AISONYA, a stunningly beautiful woman with honey-blonde hair, is Little Red Riding Hood. She is on a forest path, defiantly and fearlessly confronting a werewolf who wants to eat the food she has packed for her grandmother. She faces the fierce beast in a dynamic fighting stance, her bare legs spread wide for balance, bare muscular arms out, ready to strike. Her red cloak billows behind her as she moves in battle. The monstrous man-wolf has malevolent red eyes, its fangs slathered with drool, it's fearsome claws ready to rend and tear.", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "jpg", guidance_scale: 3, output_quality: 100, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", input={ "model": "dev", "prompt": "AISONYA, a stunningly beautiful woman with honey-blonde hair, is Little Red Riding Hood. She is on a forest path, defiantly and fearlessly confronting a werewolf who wants to eat the food she has packed for her grandmother. She faces the fierce beast in a dynamic fighting stance, her bare legs spread wide for balance, bare muscular arms out, ready to strike. Her red cloak billows behind her as she moves in battle. The monstrous man-wolf has malevolent red eyes, its fangs slathered with drool, it's fearsome claws ready to rend and tear.", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", "input": { "model": "dev", "prompt": "AISONYA, a stunningly beautiful woman with honey-blonde hair, is Little Red Riding Hood. She is on a forest path, defiantly and fearlessly confronting a werewolf who wants to eat the food she has packed for her grandmother. She faces the fierce beast in a dynamic fighting stance, her bare legs spread wide for balance, bare muscular arms out, ready to strike. Her red cloak billows behind her as she moves in battle. The monstrous man-wolf has malevolent red eyes, its fangs slathered with drool, it\'s fearsome claws ready to rend and tear.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/drrhinoai/aisonya@sha256:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a \ -i 'model="dev"' \ -i $'prompt="AISONYA, a stunningly beautiful woman with honey-blonde hair, is Little Red Riding Hood. She is on a forest path, defiantly and fearlessly confronting a werewolf who wants to eat the food she has packed for her grandmother. She faces the fierce beast in a dynamic fighting stance, her bare legs spread wide for balance, bare muscular arms out, ready to strike. Her red cloak billows behind her as she moves in battle. The monstrous man-wolf has malevolent red eyes, its fangs slathered with drool, it\'s fearsome claws ready to rend and tear."' \ -i 'go_fast=false' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="jpg"' \ -i 'guidance_scale=3' \ -i 'output_quality=100' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=28'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/drrhinoai/aisonya@sha256:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "AISONYA, a stunningly beautiful woman with honey-blonde hair, is Little Red Riding Hood. She is on a forest path, defiantly and fearlessly confronting a werewolf who wants to eat the food she has packed for her grandmother. She faces the fierce beast in a dynamic fighting stance, her bare legs spread wide for balance, bare muscular arms out, ready to strike. Her red cloak billows behind her as she moves in battle. The monstrous man-wolf has malevolent red eyes, its fangs slathered with drool, it\'s fearsome claws ready to rend and tear.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2025-01-04T22:55:46.952774Z", "created_at": "2025-01-04T22:55:36.607000Z", "data_removed": false, "error": null, "id": "5dj9wt7rkxrme0cm6e3tykp7b8", "input": { "model": "dev", "prompt": "AISONYA, a stunningly beautiful woman with honey-blonde hair, is Little Red Riding Hood. She is on a forest path, defiantly and fearlessly confronting a werewolf who wants to eat the food she has packed for her grandmother. She faces the fierce beast in a dynamic fighting stance, her bare legs spread wide for balance, bare muscular arms out, ready to strike. Her red cloak billows behind her as she moves in battle. The monstrous man-wolf has malevolent red eyes, its fangs slathered with drool, it's fearsome claws ready to rend and tear.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-01-04 22:55:36.689 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-04 22:55:36.690 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 92%|█████████▏| 281/304 [00:00<00:00, 2805.33it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2706.27it/s]\n2025-01-04 22:55:36.803 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\nfree=29311864111104\nDownloading weights\n2025-01-04T22:55:36Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpkpdssodf/weights url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar\n2025-01-04T22:55:40Z | INFO | [ Complete ] dest=/tmp/tmpkpdssodf/weights size=\"172 MB\" total_elapsed=3.837s url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar\nDownloaded weights in 3.87s\n2025-01-04 22:55:40.670 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/85bfb74a0d20402c\n2025-01-04 22:55:40.741 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-04 22:55:40.741 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-04 22:55:40.742 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 93%|█████████▎| 282/304 [00:00<00:00, 2786.89it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2685.11it/s]\n2025-01-04 22:55:40.855 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s\nUsing seed: 53910\n0it [00:00, ?it/s]\n1it [00:00, 8.37it/s]\n2it [00:00, 5.85it/s]\n3it [00:00, 5.34it/s]\n4it [00:00, 5.14it/s]\n5it [00:00, 5.01it/s]\n6it [00:01, 4.93it/s]\n7it [00:01, 4.89it/s]\n8it [00:01, 4.87it/s]\n9it [00:01, 4.85it/s]\n10it [00:01, 4.84it/s]\n11it [00:02, 4.83it/s]\n12it [00:02, 4.83it/s]\n13it [00:02, 4.83it/s]\n14it [00:02, 4.82it/s]\n15it [00:03, 4.81it/s]\n16it [00:03, 4.81it/s]\n17it [00:03, 4.81it/s]\n18it [00:03, 4.81it/s]\n19it [00:03, 4.81it/s]\n20it [00:04, 4.80it/s]\n21it [00:04, 4.81it/s]\n22it [00:04, 4.80it/s]\n23it [00:04, 4.80it/s]\n24it [00:04, 4.80it/s]\n25it [00:05, 4.79it/s]\n26it [00:05, 4.78it/s]\n27it [00:05, 4.77it/s]\n28it [00:05, 4.77it/s]\n28it [00:05, 4.88it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 10.261668649, "total_time": 10.345774 }, "output": [ "https://replicate.delivery/xezq/ZPEOgtDVLeReZkjkx65l2v5rPzbVN5FoYQYearA3piOlztDoA/out-0.jpg" ], "started_at": "2025-01-04T22:55:36.691106Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-zih5hzrri2ifw6243nhhxuwlda4v2mobkvfphc2qforkbnpzqsba", "get": "https://api.replicate.com/v1/predictions/5dj9wt7rkxrme0cm6e3tykp7b8", "cancel": "https://api.replicate.com/v1/predictions/5dj9wt7rkxrme0cm6e3tykp7b8/cancel" }, "version": "2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a" }
Generated in2025-01-04 22:55:36.689 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-04 22:55:36.690 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 92%|█████████▏| 281/304 [00:00<00:00, 2805.33it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2706.27it/s] 2025-01-04 22:55:36.803 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s free=29311864111104 Downloading weights 2025-01-04T22:55:36Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpkpdssodf/weights url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar 2025-01-04T22:55:40Z | INFO | [ Complete ] dest=/tmp/tmpkpdssodf/weights size="172 MB" total_elapsed=3.837s url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar Downloaded weights in 3.87s 2025-01-04 22:55:40.670 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/85bfb74a0d20402c 2025-01-04 22:55:40.741 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-04 22:55:40.741 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-04 22:55:40.742 | 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, 2786.89it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2685.11it/s] 2025-01-04 22:55:40.855 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s Using seed: 53910 0it [00:00, ?it/s] 1it [00:00, 8.37it/s] 2it [00:00, 5.85it/s] 3it [00:00, 5.34it/s] 4it [00:00, 5.14it/s] 5it [00:00, 5.01it/s] 6it [00:01, 4.93it/s] 7it [00:01, 4.89it/s] 8it [00:01, 4.87it/s] 9it [00:01, 4.85it/s] 10it [00:01, 4.84it/s] 11it [00:02, 4.83it/s] 12it [00:02, 4.83it/s] 13it [00:02, 4.83it/s] 14it [00:02, 4.82it/s] 15it [00:03, 4.81it/s] 16it [00:03, 4.81it/s] 17it [00:03, 4.81it/s] 18it [00:03, 4.81it/s] 19it [00:03, 4.81it/s] 20it [00:04, 4.80it/s] 21it [00:04, 4.81it/s] 22it [00:04, 4.80it/s] 23it [00:04, 4.80it/s] 24it [00:04, 4.80it/s] 25it [00:05, 4.79it/s] 26it [00:05, 4.78it/s] 27it [00:05, 4.77it/s] 28it [00:05, 4.77it/s] 28it [00:05, 4.88it/s] Total safe images: 1 out of 1
Prediction
drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28aIDqx7twvrfchrm80cm6eevsx8wvrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- AISONYA, a stunningly beautiful woman with honey-blonde hair, is Little Red Riding Hood. She is on a forest path, standing submissively and fearfully before a werewolf who wants to eat the food she has packed for her grandmother. Her body faces the camera with her eyes cast down demurely, face turned slightly away from the fierce beast, her bare legs trembling in fear, bare muscular arms held palms out, showing no malice. Her red cloak falls down her back, showing that she carries no weapons. The monstrous man-wolf has malevolent red eyes, its fangs slathered with drool, it's fearsome claws ready to rend and tear.
- go_fast
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- jpg
- guidance_scale
- 3
- output_quality
- 100
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "AISONYA, a stunningly beautiful woman with honey-blonde hair, is Little Red Riding Hood. She is on a forest path, standing submissively and fearfully before a werewolf who wants to eat the food she has packed for her grandmother. Her body faces the camera with her eyes cast down demurely, face turned slightly away from the fierce beast, her bare legs trembling in fear, bare muscular arms held palms out, showing no malice. Her red cloak falls down her back, showing that she carries no weapons. The monstrous man-wolf has malevolent red eyes, its fangs slathered with drool, it's fearsome claws ready to rend and tear.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", { input: { model: "dev", prompt: "AISONYA, a stunningly beautiful woman with honey-blonde hair, is Little Red Riding Hood. She is on a forest path, standing submissively and fearfully before a werewolf who wants to eat the food she has packed for her grandmother. Her body faces the camera with her eyes cast down demurely, face turned slightly away from the fierce beast, her bare legs trembling in fear, bare muscular arms held palms out, showing no malice. Her red cloak falls down her back, showing that she carries no weapons. The monstrous man-wolf has malevolent red eyes, its fangs slathered with drool, it's fearsome claws ready to rend and tear.", go_fast: false, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", output_format: "jpg", guidance_scale: 3, output_quality: 100, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", input={ "model": "dev", "prompt": "AISONYA, a stunningly beautiful woman with honey-blonde hair, is Little Red Riding Hood. She is on a forest path, standing submissively and fearfully before a werewolf who wants to eat the food she has packed for her grandmother. Her body faces the camera with her eyes cast down demurely, face turned slightly away from the fierce beast, her bare legs trembling in fear, bare muscular arms held palms out, showing no malice. Her red cloak falls down her back, showing that she carries no weapons. The monstrous man-wolf has malevolent red eyes, its fangs slathered with drool, it's fearsome claws ready to rend and tear.", "go_fast": False, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run drrhinoai/aisonya using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "drrhinoai/aisonya:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a", "input": { "model": "dev", "prompt": "AISONYA, a stunningly beautiful woman with honey-blonde hair, is Little Red Riding Hood. She is on a forest path, standing submissively and fearfully before a werewolf who wants to eat the food she has packed for her grandmother. Her body faces the camera with her eyes cast down demurely, face turned slightly away from the fierce beast, her bare legs trembling in fear, bare muscular arms held palms out, showing no malice. Her red cloak falls down her back, showing that she carries no weapons. The monstrous man-wolf has malevolent red eyes, its fangs slathered with drool, it\'s fearsome claws ready to rend and tear.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/drrhinoai/aisonya@sha256:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a \ -i 'model="dev"' \ -i $'prompt="AISONYA, a stunningly beautiful woman with honey-blonde hair, is Little Red Riding Hood. She is on a forest path, standing submissively and fearfully before a werewolf who wants to eat the food she has packed for her grandmother. Her body faces the camera with her eyes cast down demurely, face turned slightly away from the fierce beast, her bare legs trembling in fear, bare muscular arms held palms out, showing no malice. Her red cloak falls down her back, showing that she carries no weapons. The monstrous man-wolf has malevolent red eyes, its fangs slathered with drool, it\'s fearsome claws ready to rend and tear."' \ -i 'go_fast=false' \ -i 'lora_scale=1' \ -i 'megapixels="1"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'output_format="jpg"' \ -i 'guidance_scale=3' \ -i 'output_quality=100' \ -i 'prompt_strength=0.8' \ -i 'extra_lora_scale=1' \ -i 'num_inference_steps=28'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/drrhinoai/aisonya@sha256:2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "model": "dev", "prompt": "AISONYA, a stunningly beautiful woman with honey-blonde hair, is Little Red Riding Hood. She is on a forest path, standing submissively and fearfully before a werewolf who wants to eat the food she has packed for her grandmother. Her body faces the camera with her eyes cast down demurely, face turned slightly away from the fierce beast, her bare legs trembling in fear, bare muscular arms held palms out, showing no malice. Her red cloak falls down her back, showing that she carries no weapons. The monstrous man-wolf has malevolent red eyes, its fangs slathered with drool, it\'s fearsome claws ready to rend and tear.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2025-01-04T23:18:47.486323Z", "created_at": "2025-01-04T23:18:38.692000Z", "data_removed": false, "error": null, "id": "qx7twvrfchrm80cm6eevsx8wvr", "input": { "model": "dev", "prompt": "AISONYA, a stunningly beautiful woman with honey-blonde hair, is Little Red Riding Hood. She is on a forest path, standing submissively and fearfully before a werewolf who wants to eat the food she has packed for her grandmother. Her body faces the camera with her eyes cast down demurely, face turned slightly away from the fierce beast, her bare legs trembling in fear, bare muscular arms held palms out, showing no malice. Her red cloak falls down her back, showing that she carries no weapons. The monstrous man-wolf has malevolent red eyes, its fangs slathered with drool, it's fearsome claws ready to rend and tear.", "go_fast": false, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "jpg", "guidance_scale": 3, "output_quality": 100, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "2025-01-04 23:18:38.708 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-04 23:18:38.708 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 92%|█████████▏| 280/304 [00:00<00:00, 2788.49it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2652.27it/s]\n2025-01-04 23:18:38.823 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s\nfree=28853559140352\nDownloading weights\n2025-01-04T23:18:38Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp6gphgbfv/weights url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar\n2025-01-04T23:18:41Z | INFO | [ Complete ] dest=/tmp/tmp6gphgbfv/weights size=\"172 MB\" total_elapsed=2.417s url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar\nDownloaded weights in 2.44s\n2025-01-04 23:18:41.266 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/85bfb74a0d20402c\n2025-01-04 23:18:41.339 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-04 23:18:41.339 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-04 23:18:41.339 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 92%|█████████▏| 280/304 [00:00<00:00, 2790.52it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2654.06it/s]\n2025-01-04 23:18:41.454 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s\nUsing seed: 20485\n0it [00:00, ?it/s]\n1it [00:00, 8.38it/s]\n2it [00:00, 5.88it/s]\n3it [00:00, 5.36it/s]\n4it [00:00, 5.14it/s]\n5it [00:00, 5.02it/s]\n6it [00:01, 4.93it/s]\n7it [00:01, 4.89it/s]\n8it [00:01, 4.87it/s]\n9it [00:01, 4.86it/s]\n10it [00:01, 4.86it/s]\n11it [00:02, 4.84it/s]\n12it [00:02, 4.82it/s]\n13it [00:02, 4.82it/s]\n14it [00:02, 4.82it/s]\n15it [00:03, 4.82it/s]\n16it [00:03, 4.83it/s]\n17it [00:03, 4.82it/s]\n18it [00:03, 4.82it/s]\n19it [00:03, 4.82it/s]\n20it [00:04, 4.82it/s]\n21it [00:04, 4.81it/s]\n22it [00:04, 4.81it/s]\n23it [00:04, 4.81it/s]\n24it [00:04, 4.81it/s]\n25it [00:05, 4.81it/s]\n26it [00:05, 4.82it/s]\n27it [00:05, 4.81it/s]\n28it [00:05, 4.81it/s]\n28it [00:05, 4.89it/s]\nTotal safe images: 1 out of 1", "metrics": { "predict_time": 8.777760891, "total_time": 8.794323 }, "output": [ "https://replicate.delivery/xezq/UhnhfxlNW71nH6P6D5PnMO1aO5oW2Iw2Htvmerg8DStXP3BUA/out-0.jpg" ], "started_at": "2025-01-04T23:18:38.708562Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-32gwwxlkmzz7oj7mbeizmlpkeyrzj46prvi5vjnignsgvq64kyra", "get": "https://api.replicate.com/v1/predictions/qx7twvrfchrm80cm6eevsx8wvr", "cancel": "https://api.replicate.com/v1/predictions/qx7twvrfchrm80cm6eevsx8wvr/cancel" }, "version": "2695ce1484d8e2dcda7c0a37cb642c1ab203b08df7a3d0e178eab9cd43dda28a" }
Generated in2025-01-04 23:18:38.708 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-04 23:18:38.708 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 92%|█████████▏| 280/304 [00:00<00:00, 2788.49it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2652.27it/s] 2025-01-04 23:18:38.823 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.12s free=28853559140352 Downloading weights 2025-01-04T23:18:38Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp6gphgbfv/weights url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar 2025-01-04T23:18:41Z | INFO | [ Complete ] dest=/tmp/tmp6gphgbfv/weights size="172 MB" total_elapsed=2.417s url=https://replicate.delivery/xezq/c9mKZPlVh4IyLVD9ONCjEAUQRbJWv71sY4TsyDCIKPJIfufTA/trained_model.tar Downloaded weights in 2.44s 2025-01-04 23:18:41.266 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/85bfb74a0d20402c 2025-01-04 23:18:41.339 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded 2025-01-04 23:18:41.339 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys 2025-01-04 23:18:41.339 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 92%|█████████▏| 280/304 [00:00<00:00, 2790.52it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2654.06it/s] 2025-01-04 23:18:41.454 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.19s Using seed: 20485 0it [00:00, ?it/s] 1it [00:00, 8.38it/s] 2it [00:00, 5.88it/s] 3it [00:00, 5.36it/s] 4it [00:00, 5.14it/s] 5it [00:00, 5.02it/s] 6it [00:01, 4.93it/s] 7it [00:01, 4.89it/s] 8it [00:01, 4.87it/s] 9it [00:01, 4.86it/s] 10it [00:01, 4.86it/s] 11it [00:02, 4.84it/s] 12it [00:02, 4.82it/s] 13it [00:02, 4.82it/s] 14it [00:02, 4.82it/s] 15it [00:03, 4.82it/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, 4.81it/s] 22it [00:04, 4.81it/s] 23it [00:04, 4.81it/s] 24it [00:04, 4.81it/s] 25it [00:05, 4.81it/s] 26it [00:05, 4.82it/s] 27it [00:05, 4.81it/s] 28it [00:05, 4.81it/s] 28it [00:05, 4.89it/s] Total safe images: 1 out of 1
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