lucataco / sdxl-lcm
Latent Consistency Model (LCM): SDXL, distills the original model into a version that requires fewer steps (4 to 8 instead of the original 25 to 50)
Prediction
lucataco/sdxl-lcm:e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4IDqsqxt73b5uiaf4yzztpmoqywseStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedby @lucatacoInput
- seed
- 48373
- width
- 1024
- height
- 1024
- prompt
- A studio photo of a rainbow coloured cat
- scheduler
- LCM
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 2
- apply_watermark
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 6
{ "seed": 48373, "width": 1024, "height": 1024, "prompt": "A studio photo of a rainbow coloured cat", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/sdxl-lcm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/sdxl-lcm:e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4", { input: { seed: 48373, width: 1024, height: 1024, prompt: "A studio photo of a rainbow coloured cat", scheduler: "LCM", lora_scale: 0.6, num_outputs: 1, guidance_scale: 2, apply_watermark: true, negative_prompt: "", prompt_strength: 0.8, num_inference_steps: 6 } } ); // 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 lucataco/sdxl-lcm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/sdxl-lcm:e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4", input={ "seed": 48373, "width": 1024, "height": 1024, "prompt": "A studio photo of a rainbow coloured cat", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": True, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/sdxl-lcm 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": "lucataco/sdxl-lcm:e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4", "input": { "seed": 48373, "width": 1024, "height": 1024, "prompt": "A studio photo of a rainbow coloured cat", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-12T17:20:09.713308Z", "created_at": "2023-11-12T17:20:06.393614Z", "data_removed": false, "error": null, "id": "qsqxt73b5uiaf4yzztpmoqywse", "input": { "seed": 48373, "width": 1024, "height": 1024, "prompt": "A studio photo of a rainbow coloured cat", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 }, "logs": "Using seed: 48373\nPrompt: A studio photo of a rainbow coloured cat\ntxt2img mode\nThe config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n 0%| | 0/6 [00:00<?, ?it/s]\n 17%|█▋ | 1/6 [00:00<00:01, 4.96it/s]\n 33%|███▎ | 2/6 [00:00<00:00, 4.94it/s]\n 50%|█████ | 3/6 [00:00<00:00, 4.93it/s]\n 67%|██████▋ | 4/6 [00:00<00:00, 4.92it/s]\n 83%|████████▎ | 5/6 [00:01<00:00, 4.91it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.90it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.91it/s]", "metrics": { "predict_time": 3.329261, "total_time": 3.319694 }, "output": [ "https://replicate.delivery/pbxt/IeEVsbcvowQFBC46A0iHuYdTwWbOpvgGrU85AhHaP9Dk217IA/out-0.png" ], "started_at": "2023-11-12T17:20:06.384047Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/qsqxt73b5uiaf4yzztpmoqywse", "cancel": "https://api.replicate.com/v1/predictions/qsqxt73b5uiaf4yzztpmoqywse/cancel" }, "version": "e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4" }Generated inUsing seed: 48373 Prompt: A studio photo of a rainbow coloured cat txt2img mode The config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. 0%| | 0/6 [00:00<?, ?it/s] 17%|█▋ | 1/6 [00:00<00:01, 4.96it/s] 33%|███▎ | 2/6 [00:00<00:00, 4.94it/s] 50%|█████ | 3/6 [00:00<00:00, 4.93it/s] 67%|██████▋ | 4/6 [00:00<00:00, 4.92it/s] 83%|████████▎ | 5/6 [00:01<00:00, 4.91it/s] 100%|██████████| 6/6 [00:01<00:00, 4.90it/s] 100%|██████████| 6/6 [00:01<00:00, 4.91it/s]Prediction
lucataco/sdxl-lcm:e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4IDgs2hrhdb4e3poez7f66peyp6umStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 58684
- width
- 1248
- height
- 832
- prompt
- A beautiful landscape photo, cinematic
- scheduler
- LCM
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 2
- apply_watermark
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 6
{ "seed": 58684, "width": 1248, "height": 832, "prompt": "A beautiful landscape photo, cinematic", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/sdxl-lcm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/sdxl-lcm:e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4", { input: { seed: 58684, width: 1248, height: 832, prompt: "A beautiful landscape photo, cinematic", scheduler: "LCM", lora_scale: 0.6, num_outputs: 1, guidance_scale: 2, apply_watermark: true, negative_prompt: "", prompt_strength: 0.8, num_inference_steps: 6 } } ); // 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 lucataco/sdxl-lcm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/sdxl-lcm:e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4", input={ "seed": 58684, "width": 1248, "height": 832, "prompt": "A beautiful landscape photo, cinematic", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": True, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/sdxl-lcm 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": "lucataco/sdxl-lcm:e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4", "input": { "seed": 58684, "width": 1248, "height": 832, "prompt": "A beautiful landscape photo, cinematic", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-12T17:22:17.446784Z", "created_at": "2023-11-12T17:22:14.130127Z", "data_removed": false, "error": null, "id": "gs2hrhdb4e3poez7f66peyp6um", "input": { "seed": 58684, "width": 1248, "height": 832, "prompt": "A beautiful landscape photo, cinematic", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 }, "logs": "Using seed: 58684\nPrompt: A beautiful landscape photo, cinematic\ntxt2img mode\nThe config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n 0%| | 0/6 [00:00<?, ?it/s]\n 17%|█▋ | 1/6 [00:00<00:00, 5.01it/s]\n 33%|███▎ | 2/6 [00:00<00:00, 4.98it/s]\n 50%|█████ | 3/6 [00:00<00:00, 4.97it/s]\n 67%|██████▋ | 4/6 [00:00<00:00, 4.96it/s]\n 83%|████████▎ | 5/6 [00:01<00:00, 4.93it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.93it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.94it/s]", "metrics": { "predict_time": 3.321141, "total_time": 3.316657 }, "output": [ "https://replicate.delivery/pbxt/NrZAqBf61aVxHqLKmC941NkktkIOJC6YZqWteCKUtKLIvr3RA/out-0.png" ], "started_at": "2023-11-12T17:22:14.125643Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/gs2hrhdb4e3poez7f66peyp6um", "cancel": "https://api.replicate.com/v1/predictions/gs2hrhdb4e3poez7f66peyp6um/cancel" }, "version": "e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4" }Generated inUsing seed: 58684 Prompt: A beautiful landscape photo, cinematic txt2img mode The config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. 0%| | 0/6 [00:00<?, ?it/s] 17%|█▋ | 1/6 [00:00<00:00, 5.01it/s] 33%|███▎ | 2/6 [00:00<00:00, 4.98it/s] 50%|█████ | 3/6 [00:00<00:00, 4.97it/s] 67%|██████▋ | 4/6 [00:00<00:00, 4.96it/s] 83%|████████▎ | 5/6 [00:01<00:00, 4.93it/s] 100%|██████████| 6/6 [00:01<00:00, 4.93it/s] 100%|██████████| 6/6 [00:01<00:00, 4.94it/s]Prediction
lucataco/sdxl-lcm:e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4IDroonubtbesgwbxriccu6do2t4eStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 47500
- image
- width
- 1024
- height
- 1024
- prompt
- A rainbow coloured tiger
- scheduler
- LCM
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 2
- apply_watermark
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 6
{ "seed": 47500, "image": "https://replicate.delivery/pbxt/JrhlPJFfdYFHZjT5M7QNZg3dLnFbR25gfgwbMOA6Mm03WFZn/cat-sdxl.png", "width": 1024, "height": 1024, "prompt": "A rainbow coloured tiger", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/sdxl-lcm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/sdxl-lcm:e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4", { input: { seed: 47500, image: "https://replicate.delivery/pbxt/JrhlPJFfdYFHZjT5M7QNZg3dLnFbR25gfgwbMOA6Mm03WFZn/cat-sdxl.png", width: 1024, height: 1024, prompt: "A rainbow coloured tiger", scheduler: "LCM", lora_scale: 0.6, num_outputs: 1, guidance_scale: 2, apply_watermark: true, negative_prompt: "", prompt_strength: 0.8, num_inference_steps: 6 } } ); // 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 lucataco/sdxl-lcm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/sdxl-lcm:e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4", input={ "seed": 47500, "image": "https://replicate.delivery/pbxt/JrhlPJFfdYFHZjT5M7QNZg3dLnFbR25gfgwbMOA6Mm03WFZn/cat-sdxl.png", "width": 1024, "height": 1024, "prompt": "A rainbow coloured tiger", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": True, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/sdxl-lcm 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": "lucataco/sdxl-lcm:e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4", "input": { "seed": 47500, "image": "https://replicate.delivery/pbxt/JrhlPJFfdYFHZjT5M7QNZg3dLnFbR25gfgwbMOA6Mm03WFZn/cat-sdxl.png", "width": 1024, "height": 1024, "prompt": "A rainbow coloured tiger", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-12T17:23:36.978946Z", "created_at": "2023-11-12T17:23:33.265086Z", "data_removed": false, "error": null, "id": "roonubtbesgwbxriccu6do2t4e", "input": { "seed": 47500, "image": "https://replicate.delivery/pbxt/JrhlPJFfdYFHZjT5M7QNZg3dLnFbR25gfgwbMOA6Mm03WFZn/cat-sdxl.png", "width": 1024, "height": 1024, "prompt": "A rainbow coloured tiger", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 }, "logs": "Using seed: 47500\nPrompt: A rainbow coloured tiger\nimg2img mode\nThe config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n 0%| | 0/4 [00:00<?, ?it/s]\n 25%|██▌ | 1/4 [00:00<00:00, 4.95it/s]\n 50%|█████ | 2/4 [00:00<00:00, 4.93it/s]\n 75%|███████▌ | 3/4 [00:00<00:00, 4.93it/s]\n100%|██████████| 4/4 [00:00<00:00, 4.93it/s]\n100%|██████████| 4/4 [00:00<00:00, 4.93it/s]", "metrics": { "predict_time": 3.746818, "total_time": 3.71386 }, "output": [ "https://replicate.delivery/pbxt/o8ocDIdP5pqzBFekuhEdMrd5aR9epOuCfPvTGeMWH5PjBveOC/out-0.png" ], "started_at": "2023-11-12T17:23:33.232128Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/roonubtbesgwbxriccu6do2t4e", "cancel": "https://api.replicate.com/v1/predictions/roonubtbesgwbxriccu6do2t4e/cancel" }, "version": "e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4" }Generated inUsing seed: 47500 Prompt: A rainbow coloured tiger img2img mode The config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:00, 4.95it/s] 50%|█████ | 2/4 [00:00<00:00, 4.93it/s] 75%|███████▌ | 3/4 [00:00<00:00, 4.93it/s] 100%|██████████| 4/4 [00:00<00:00, 4.93it/s] 100%|██████████| 4/4 [00:00<00:00, 4.93it/s]Prediction
lucataco/sdxl-lcm:e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4IDzjx7ah3bpzllwwjoh65fkklnheStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- mask
- seed
- 42283
- image
- width
- 1024
- height
- 1024
- prompt
- Alien invasion in NYC
- scheduler
- LCM
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 2
- apply_watermark
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 6
{ "mask": "https://replicate.delivery/pbxt/JrhnxENes0tqGJ0wgAW2XiQYXVKhXM4yb6lV803HNNbwwq10/nyc-mask.png", "seed": 42283, "image": "https://replicate.delivery/pbxt/JrhnxdM7pPc0eRAI25y3KeT6uh2wsH4TrZIjql9SlLMjCnyJ/nyc.png", "width": 1024, "height": 1024, "prompt": "Alien invasion in NYC", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/sdxl-lcm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/sdxl-lcm:e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4", { input: { mask: "https://replicate.delivery/pbxt/JrhnxENes0tqGJ0wgAW2XiQYXVKhXM4yb6lV803HNNbwwq10/nyc-mask.png", seed: 42283, image: "https://replicate.delivery/pbxt/JrhnxdM7pPc0eRAI25y3KeT6uh2wsH4TrZIjql9SlLMjCnyJ/nyc.png", width: 1024, height: 1024, prompt: "Alien invasion in NYC", scheduler: "LCM", lora_scale: 0.6, num_outputs: 1, guidance_scale: 2, apply_watermark: true, negative_prompt: "", prompt_strength: 0.8, num_inference_steps: 6 } } ); // 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 lucataco/sdxl-lcm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/sdxl-lcm:e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4", input={ "mask": "https://replicate.delivery/pbxt/JrhnxENes0tqGJ0wgAW2XiQYXVKhXM4yb6lV803HNNbwwq10/nyc-mask.png", "seed": 42283, "image": "https://replicate.delivery/pbxt/JrhnxdM7pPc0eRAI25y3KeT6uh2wsH4TrZIjql9SlLMjCnyJ/nyc.png", "width": 1024, "height": 1024, "prompt": "Alien invasion in NYC", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": True, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/sdxl-lcm 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": "lucataco/sdxl-lcm:e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4", "input": { "mask": "https://replicate.delivery/pbxt/JrhnxENes0tqGJ0wgAW2XiQYXVKhXM4yb6lV803HNNbwwq10/nyc-mask.png", "seed": 42283, "image": "https://replicate.delivery/pbxt/JrhnxdM7pPc0eRAI25y3KeT6uh2wsH4TrZIjql9SlLMjCnyJ/nyc.png", "width": 1024, "height": 1024, "prompt": "Alien invasion in NYC", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-12T17:26:18.311879Z", "created_at": "2023-11-12T17:26:14.062643Z", "data_removed": false, "error": null, "id": "zjx7ah3bpzllwwjoh65fkklnhe", "input": { "mask": "https://replicate.delivery/pbxt/JrhnxENes0tqGJ0wgAW2XiQYXVKhXM4yb6lV803HNNbwwq10/nyc-mask.png", "seed": 42283, "image": "https://replicate.delivery/pbxt/JrhnxdM7pPc0eRAI25y3KeT6uh2wsH4TrZIjql9SlLMjCnyJ/nyc.png", "width": 1024, "height": 1024, "prompt": "Alien invasion in NYC", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 }, "logs": "Using seed: 42283\nPrompt: Alien invasion in NYC\ninpainting mode\nThe config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n 0%| | 0/4 [00:00<?, ?it/s]\n 25%|██▌ | 1/4 [00:00<00:00, 4.92it/s]\n 50%|█████ | 2/4 [00:00<00:00, 4.91it/s]\n 75%|███████▌ | 3/4 [00:00<00:00, 4.91it/s]\n100%|██████████| 4/4 [00:00<00:00, 4.91it/s]\n100%|██████████| 4/4 [00:00<00:00, 4.91it/s]", "metrics": { "predict_time": 4.255648, "total_time": 4.249236 }, "output": [ "https://replicate.delivery/pbxt/82L3U0aIAHoZFhzSwnfjBn1ykOjAmAKnvTsnxqfkfA3zlXvjA/out-0.png" ], "started_at": "2023-11-12T17:26:14.056231Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/zjx7ah3bpzllwwjoh65fkklnhe", "cancel": "https://api.replicate.com/v1/predictions/zjx7ah3bpzllwwjoh65fkklnhe/cancel" }, "version": "e9e25ca4176eb9f7b92994670e7c40e85910118c3f2370213c136046ec0774a4" }Generated inUsing seed: 42283 Prompt: Alien invasion in NYC inpainting mode The config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:00, 4.92it/s] 50%|█████ | 2/4 [00:00<00:00, 4.91it/s] 75%|███████▌ | 3/4 [00:00<00:00, 4.91it/s] 100%|██████████| 4/4 [00:00<00:00, 4.91it/s] 100%|██████████| 4/4 [00:00<00:00, 4.91it/s]Prediction
lucataco/sdxl-lcm:fbbd475b1084de80c47c35bfe4ae64b964294aa7e237e6537eed938cfd24903dIDzn3e3ctb7zixnch5xz37exafuyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 16010
- width
- 1024
- height
- 1024
- prompt
- An astronaut riding a rainbow unicorn, cinematic, dramatic
- scheduler
- LCM
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 2
- apply_watermark
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 6
{ "seed": 16010, "width": 1024, "height": 1024, "prompt": "An astronaut riding a rainbow unicorn, cinematic, dramatic", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/sdxl-lcm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/sdxl-lcm:fbbd475b1084de80c47c35bfe4ae64b964294aa7e237e6537eed938cfd24903d", { input: { seed: 16010, width: 1024, height: 1024, prompt: "An astronaut riding a rainbow unicorn, cinematic, dramatic", scheduler: "LCM", lora_scale: 0.6, num_outputs: 1, guidance_scale: 2, apply_watermark: true, negative_prompt: "", prompt_strength: 0.8, num_inference_steps: 6 } } ); // 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 lucataco/sdxl-lcm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/sdxl-lcm:fbbd475b1084de80c47c35bfe4ae64b964294aa7e237e6537eed938cfd24903d", input={ "seed": 16010, "width": 1024, "height": 1024, "prompt": "An astronaut riding a rainbow unicorn, cinematic, dramatic", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": True, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/sdxl-lcm 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": "lucataco/sdxl-lcm:fbbd475b1084de80c47c35bfe4ae64b964294aa7e237e6537eed938cfd24903d", "input": { "seed": 16010, "width": 1024, "height": 1024, "prompt": "An astronaut riding a rainbow unicorn, cinematic, dramatic", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-13T02:28:58.391101Z", "created_at": "2023-11-13T02:28:10.415705Z", "data_removed": false, "error": null, "id": "zn3e3ctb7zixnch5xz37exafuy", "input": { "seed": 16010, "width": 1024, "height": 1024, "prompt": "An astronaut riding a rainbow unicorn, cinematic, dramatic", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 2, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 6 }, "logs": "Using seed: 16010\nPrompt: An astronaut riding a rainbow unicorn, cinematic, dramatic\ntxt2img mode\nThe config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n 0%| | 0/6 [00:00<?, ?it/s]\n 17%|█▋ | 1/6 [00:00<00:04, 1.20it/s]\n 33%|███▎ | 2/6 [00:01<00:01, 2.17it/s]\n 50%|█████ | 3/6 [00:01<00:01, 2.93it/s]\n 67%|██████▋ | 4/6 [00:01<00:00, 3.51it/s]\n 83%|████████▎ | 5/6 [00:01<00:00, 3.93it/s]\n100%|██████████| 6/6 [00:01<00:00, 4.24it/s]\n100%|██████████| 6/6 [00:01<00:00, 3.27it/s]", "metrics": { "predict_time": 3.606804, "total_time": 47.975396 }, "output": [ "https://replicate.delivery/pbxt/Le5OsDPb5NQ4JqfbU14fiYVP0uVqAKuf9F94oni4V5PkededE/out-0.png" ], "started_at": "2023-11-13T02:28:54.784297Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/zn3e3ctb7zixnch5xz37exafuy", "cancel": "https://api.replicate.com/v1/predictions/zn3e3ctb7zixnch5xz37exafuy/cancel" }, "version": "fbbd475b1084de80c47c35bfe4ae64b964294aa7e237e6537eed938cfd24903d" }Generated inUsing seed: 16010 Prompt: An astronaut riding a rainbow unicorn, cinematic, dramatic txt2img mode The config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. 0%| | 0/6 [00:00<?, ?it/s] 17%|█▋ | 1/6 [00:00<00:04, 1.20it/s] 33%|███▎ | 2/6 [00:01<00:01, 2.17it/s] 50%|█████ | 3/6 [00:01<00:01, 2.93it/s] 67%|██████▋ | 4/6 [00:01<00:00, 3.51it/s] 83%|████████▎ | 5/6 [00:01<00:00, 3.93it/s] 100%|██████████| 6/6 [00:01<00:00, 4.24it/s] 100%|██████████| 6/6 [00:01<00:00, 3.27it/s]Prediction
lucataco/sdxl-lcm:fbbd475b1084de80c47c35bfe4ae64b964294aa7e237e6537eed938cfd24903dIDx0cwyhz955rma0ckkq9rwsdma4StatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- seed
- 29070
- width
- 1024
- height
- 1024
- prompt
- close-up photography of a panda standing in the rain at night in a yellow jacket, under a clear umbrella, urban setting, in a street lit by lamps, facing camera, leica 35mm summilux
- scheduler
- LCM
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 1
- apply_watermark
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 4
{ "seed": 29070, "width": 1024, "height": 1024, "prompt": "close-up photography of a panda standing in the rain at night in a yellow jacket, under a clear umbrella, urban setting, in a street lit by lamps, facing camera, leica 35mm summilux", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 1, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 4 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/sdxl-lcm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/sdxl-lcm:fbbd475b1084de80c47c35bfe4ae64b964294aa7e237e6537eed938cfd24903d", { input: { seed: 29070, width: 1024, height: 1024, prompt: "close-up photography of a panda standing in the rain at night in a yellow jacket, under a clear umbrella, urban setting, in a street lit by lamps, facing camera, leica 35mm summilux", scheduler: "LCM", lora_scale: 0.6, num_outputs: 1, guidance_scale: 1, apply_watermark: true, negative_prompt: "", prompt_strength: 0.8, num_inference_steps: 4 } } ); // 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 lucataco/sdxl-lcm using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/sdxl-lcm:fbbd475b1084de80c47c35bfe4ae64b964294aa7e237e6537eed938cfd24903d", input={ "seed": 29070, "width": 1024, "height": 1024, "prompt": "close-up photography of a panda standing in the rain at night in a yellow jacket, under a clear umbrella, urban setting, in a street lit by lamps, facing camera, leica 35mm summilux", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 1, "apply_watermark": True, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 4 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/sdxl-lcm 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": "lucataco/sdxl-lcm:fbbd475b1084de80c47c35bfe4ae64b964294aa7e237e6537eed938cfd24903d", "input": { "seed": 29070, "width": 1024, "height": 1024, "prompt": "close-up photography of a panda standing in the rain at night in a yellow jacket, under a clear umbrella, urban setting, in a street lit by lamps, facing camera, leica 35mm summilux", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 1, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 4 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-12-06T21:16:37.410075Z", "created_at": "2024-12-06T21:15:30.985000Z", "data_removed": false, "error": null, "id": "x0cwyhz955rma0ckkq9rwsdma4", "input": { "seed": 29070, "width": 1024, "height": 1024, "prompt": "close-up photography of a panda standing in the rain at night in a yellow jacket, under a clear umbrella, urban setting, in a street lit by lamps, facing camera, leica 35mm summilux", "scheduler": "LCM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 1, "apply_watermark": true, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 4 }, "logs": "Using seed: 29070\nPrompt: close-up photography of a panda standing in the rain at night in a yellow jacket, under a clear umbrella, urban setting, in a street lit by lamps, facing camera, leica 35mm summilux\ntxt2img mode\nThe config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n 0%| | 0/4 [00:00<?, ?it/s]\n 25%|██▌ | 1/4 [00:00<00:00, 5.64it/s]\n 75%|███████▌ | 3/4 [00:00<00:00, 11.00it/s]\n100%|██████████| 4/4 [00:00<00:00, 11.11it/s]", "metrics": { "predict_time": 1.294088758, "total_time": 66.425075 }, "output": [ "https://replicate.delivery/xezq/CFULEO2b1eX9XKslkybMQhQLatPS79fBwMTles4k77lqdjwnA/out-0.png" ], "started_at": "2024-12-06T21:16:36.115986Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-io5mndnonhmajwh7s5f44wihmd63d3gbo3qv3dcmj3jhyrmukuta", "get": "https://api.replicate.com/v1/predictions/x0cwyhz955rma0ckkq9rwsdma4", "cancel": "https://api.replicate.com/v1/predictions/x0cwyhz955rma0ckkq9rwsdma4/cancel" }, "version": "fbbd475b1084de80c47c35bfe4ae64b964294aa7e237e6537eed938cfd24903d" }Generated inUsing seed: 29070 Prompt: close-up photography of a panda standing in the rain at night in a yellow jacket, under a clear umbrella, urban setting, in a street lit by lamps, facing camera, leica 35mm summilux txt2img mode The config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file. 0%| | 0/4 [00:00<?, ?it/s] 25%|██▌ | 1/4 [00:00<00:00, 5.64it/s] 75%|███████▌ | 3/4 [00:00<00:00, 11.00it/s] 100%|██████████| 4/4 [00:00<00:00, 11.11it/s]
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