fofr / sdxl-abstract
(Updated 1 year, 8 months ago)
- Public
- 1.5K runs
- SDXL fine-tune
Prediction
fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03IDwt2oyolbsu3h7q7u4daidh7cvaStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 768
- height
- 1152
- prompt
- A TOK abstract photo
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 768, "height": 1152, "prompt": "A TOK abstract photo", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 }Install Replicate’s Node.js client library:npm install replicateImport 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 fofr/sdxl-abstract using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03", { input: { width: 768, height: 1152, prompt: "A TOK abstract photo", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.8, negative_prompt: "", prompt_strength: 0.8, num_inference_steps: 30 } } ); // 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 replicateImport the client:import replicateRun fofr/sdxl-abstract using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03", input={ "width": 768, "height": 1152, "prompt": "A TOK abstract photo", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run fofr/sdxl-abstract 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": "fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03", "input": { "width": 768, "height": 1152, "prompt": "A TOK abstract photo", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo 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 cogIf 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/fofr/sdxl-abstract@sha256:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03 \ -i 'width=768' \ -i 'height=1152' \ -i 'prompt="A TOK abstract photo"' \ -i 'refine="expert_ensemble_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.6' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=false' \ -i 'high_noise_frac=0.8' \ -i 'negative_prompt=""' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=30'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/fofr/sdxl-abstract@sha256:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 768, "height": 1152, "prompt": "A TOK abstract photo", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2023-09-23T05:01:39.781768Z", "created_at": "2023-09-23T05:01:29.901978Z", "data_removed": false, "error": null, "id": "wt2oyolbsu3h7q7u4daidh7cva", "input": { "width": 768, "height": 1152, "prompt": "A TOK abstract photo", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": null, "metrics": { "predict_time": 8.700355, "total_time": 9.87979 }, "output": [ "https://replicate.delivery/pbxt/8g9HzRPvFdLOIxkYH6Nse4RBRiHM7vsDRHBzRq88VwiZGhzIA/out-0.png" ], "started_at": "2023-09-23T05:01:31.081413Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/wt2oyolbsu3h7q7u4daidh7cva", "cancel": "https://api.replicate.com/v1/predictions/wt2oyolbsu3h7q7u4daidh7cva/cancel" }, "version": "a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03" }Prediction
fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03IDdtk36k3b2j7qqmna6da45bshqyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 768
- height
- 1152
- prompt
- A TOK abstract photo, red and cityscape
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.62
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.9
- negative_prompt
- muted
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 768, "height": 1152, "prompt": "A TOK abstract photo, red and cityscape", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.62, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "muted", "prompt_strength": 0.8, "num_inference_steps": 30 }Install Replicate’s Node.js client library:npm install replicateImport 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 fofr/sdxl-abstract using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03", { input: { width: 768, height: 1152, prompt: "A TOK abstract photo, red and cityscape", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.62, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.9, negative_prompt: "muted", prompt_strength: 0.8, num_inference_steps: 30 } } ); // 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 replicateImport the client:import replicateRun fofr/sdxl-abstract using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03", input={ "width": 768, "height": 1152, "prompt": "A TOK abstract photo, red and cityscape", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.62, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.9, "negative_prompt": "muted", "prompt_strength": 0.8, "num_inference_steps": 30 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run fofr/sdxl-abstract 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": "fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03", "input": { "width": 768, "height": 1152, "prompt": "A TOK abstract photo, red and cityscape", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.62, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "muted", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo 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 cogIf 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/fofr/sdxl-abstract@sha256:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03 \ -i 'width=768' \ -i 'height=1152' \ -i 'prompt="A TOK abstract photo, red and cityscape"' \ -i 'refine="expert_ensemble_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.62' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=false' \ -i 'high_noise_frac=0.9' \ -i 'negative_prompt="muted"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=30'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/fofr/sdxl-abstract@sha256:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 768, "height": 1152, "prompt": "A TOK abstract photo, red and cityscape", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.62, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "muted", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2023-09-23T05:06:22.344011Z", "created_at": "2023-09-23T05:06:13.515920Z", "data_removed": false, "error": null, "id": "dtk36k3b2j7qqmna6da45bshqy", "input": { "width": 768, "height": 1152, "prompt": "A TOK abstract photo, red and cityscape", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.62, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "muted", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": null, "metrics": { "predict_time": 7.969978, "total_time": 8.828091 }, "output": [ "https://replicate.delivery/pbxt/9oNrH7nOVWa6H9ZIuLQYpX1H12PjLC8L4k7YcBfnjTvmIhzIA/out-0.png" ], "started_at": "2023-09-23T05:06:14.374033Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/dtk36k3b2j7qqmna6da45bshqy", "cancel": "https://api.replicate.com/v1/predictions/dtk36k3b2j7qqmna6da45bshqy/cancel" }, "version": "a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03" }Prediction
fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03IDib57dmlbbnhd526p5ydji2elc4StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 768
- height
- 1152
- prompt
- A TOK abstract photo, red and cityscape
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.62
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.9
- negative_prompt
- muted
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 768, "height": 1152, "prompt": "A TOK abstract photo, red and cityscape", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.62, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "muted", "prompt_strength": 0.8, "num_inference_steps": 30 }Install Replicate’s Node.js client library:npm install replicateImport 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 fofr/sdxl-abstract using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03", { input: { width: 768, height: 1152, prompt: "A TOK abstract photo, red and cityscape", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.62, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.9, negative_prompt: "muted", prompt_strength: 0.8, num_inference_steps: 30 } } ); // 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 replicateImport the client:import replicateRun fofr/sdxl-abstract using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03", input={ "width": 768, "height": 1152, "prompt": "A TOK abstract photo, red and cityscape", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.62, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.9, "negative_prompt": "muted", "prompt_strength": 0.8, "num_inference_steps": 30 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run fofr/sdxl-abstract 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": "fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03", "input": { "width": 768, "height": 1152, "prompt": "A TOK abstract photo, red and cityscape", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.62, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "muted", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo 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 cogIf 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/fofr/sdxl-abstract@sha256:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03 \ -i 'width=768' \ -i 'height=1152' \ -i 'prompt="A TOK abstract photo, red and cityscape"' \ -i 'refine="expert_ensemble_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.62' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=false' \ -i 'high_noise_frac=0.9' \ -i 'negative_prompt="muted"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=30'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/fofr/sdxl-abstract@sha256:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 768, "height": 1152, "prompt": "A TOK abstract photo, red and cityscape", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.62, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "muted", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2023-09-23T05:07:12.271032Z", "created_at": "2023-09-23T05:07:02.385021Z", "data_removed": false, "error": null, "id": "ib57dmlbbnhd526p5ydji2elc4", "input": { "width": 768, "height": 1152, "prompt": "A TOK abstract photo, red and cityscape", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.62, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "muted", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": null, "metrics": { "predict_time": 8.854878, "total_time": 9.886011 }, "output": [ "https://replicate.delivery/pbxt/iuwaqCLX04I7KxISrh0XbsW0YckOU5QK1wVoEwf45jffjEOjA/out-0.png" ], "started_at": "2023-09-23T05:07:03.416154Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ib57dmlbbnhd526p5ydji2elc4", "cancel": "https://api.replicate.com/v1/predictions/ib57dmlbbnhd526p5ydji2elc4/cancel" }, "version": "a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03" }Prediction
fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03IDcfjfrn3bxtoq7tukupcmbu32mmStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 768
- height
- 1152
- prompt
- A TOK abstract photo, portrait photo of a woman
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.62
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.9
- negative_prompt
- muted
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 768, "height": 1152, "prompt": "A TOK abstract photo, portrait photo of a woman", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.62, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "muted", "prompt_strength": 0.8, "num_inference_steps": 30 }Install Replicate’s Node.js client library:npm install replicateImport 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 fofr/sdxl-abstract using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03", { input: { width: 768, height: 1152, prompt: "A TOK abstract photo, portrait photo of a woman", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.62, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.9, negative_prompt: "muted", prompt_strength: 0.8, num_inference_steps: 30 } } ); // 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 replicateImport the client:import replicateRun fofr/sdxl-abstract using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03", input={ "width": 768, "height": 1152, "prompt": "A TOK abstract photo, portrait photo of a woman", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.62, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.9, "negative_prompt": "muted", "prompt_strength": 0.8, "num_inference_steps": 30 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run fofr/sdxl-abstract 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": "fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03", "input": { "width": 768, "height": 1152, "prompt": "A TOK abstract photo, portrait photo of a woman", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.62, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "muted", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo 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 cogIf 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/fofr/sdxl-abstract@sha256:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03 \ -i 'width=768' \ -i 'height=1152' \ -i 'prompt="A TOK abstract photo, portrait photo of a woman"' \ -i 'refine="expert_ensemble_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.62' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=false' \ -i 'high_noise_frac=0.9' \ -i 'negative_prompt="muted"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=30'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/fofr/sdxl-abstract@sha256:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 768, "height": 1152, "prompt": "A TOK abstract photo, portrait photo of a woman", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.62, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "muted", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2023-09-23T05:08:41.607548Z", "created_at": "2023-09-23T05:08:32.681043Z", "data_removed": false, "error": null, "id": "cfjfrn3bxtoq7tukupcmbu32mm", "input": { "width": 768, "height": 1152, "prompt": "A TOK abstract photo, portrait photo of a woman", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.62, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.9, "negative_prompt": "muted", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": null, "metrics": { "predict_time": 8.271519, "total_time": 8.926505 }, "output": [ "https://replicate.delivery/pbxt/AMomt5qo9AafIy4AFDqcCTzASu3VJdscGZT21Vb1gieZTCnRA/out-0.png" ], "started_at": "2023-09-23T05:08:33.336029Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/cfjfrn3bxtoq7tukupcmbu32mm", "cancel": "https://api.replicate.com/v1/predictions/cfjfrn3bxtoq7tukupcmbu32mm/cancel" }, "version": "a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03" }Prediction
fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03IDle4slldbnophixkjkp3aombg7aStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- A red abstract TOK photo, cityscape, cat
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- muted, ugly, broken, disfigured
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 1024, "height": 1024, "prompt": "A red abstract TOK photo, cityscape, cat", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "muted, ugly, broken, disfigured", "prompt_strength": 0.8, "num_inference_steps": 30 }Install Replicate’s Node.js client library:npm install replicateImport 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 fofr/sdxl-abstract using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03", { input: { width: 1024, height: 1024, prompt: "A red abstract TOK photo, cityscape, cat", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.8, negative_prompt: "muted, ugly, broken, disfigured", prompt_strength: 0.8, num_inference_steps: 30 } } ); // 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 replicateImport the client:import replicateRun fofr/sdxl-abstract using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03", input={ "width": 1024, "height": 1024, "prompt": "A red abstract TOK photo, cityscape, cat", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.8, "negative_prompt": "muted, ugly, broken, disfigured", "prompt_strength": 0.8, "num_inference_steps": 30 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run fofr/sdxl-abstract 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": "fofr/sdxl-abstract:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03", "input": { "width": 1024, "height": 1024, "prompt": "A red abstract TOK photo, cityscape, cat", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "muted, ugly, broken, disfigured", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo 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 cogIf 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/fofr/sdxl-abstract@sha256:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03 \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="A red abstract TOK photo, cityscape, cat"' \ -i 'refine="expert_ensemble_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.6' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=false' \ -i 'high_noise_frac=0.8' \ -i 'negative_prompt="muted, ugly, broken, disfigured"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=30'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/fofr/sdxl-abstract@sha256:a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "A red abstract TOK photo, cityscape, cat", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "muted, ugly, broken, disfigured", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2023-09-23T05:23:04.642819Z", "created_at": "2023-09-23T05:22:55.501975Z", "data_removed": false, "error": null, "id": "le4slldbnophixkjkp3aombg7a", "input": { "width": 1024, "height": 1024, "prompt": "A red abstract TOK photo, cityscape, cat", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "muted, ugly, broken, disfigured", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": null, "metrics": { "predict_time": 8.014212, "total_time": 9.140844 }, "output": [ "https://replicate.delivery/pbxt/QHZo5rDe6MRwVamruav2N3otleKj6VBszyoSR9cujxg4gCnRA/out-0.png" ], "started_at": "2023-09-23T05:22:56.628607Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/le4slldbnophixkjkp3aombg7a", "cancel": "https://api.replicate.com/v1/predictions/le4slldbnophixkjkp3aombg7a/cancel" }, "version": "a28d461dc16846310d03d12f8cbc31c5ef487356aa7b48ac1709969418768a03" }
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