swartype
/
sdxl-pixar
Create Pixar poster easily with SDXL Pixar.
- Public
- 633.7K runs
-
L40S
- SDXL fine-tune
Prediction
swartype/sdxl-pixar:81f8bbd3IDv2qfjotbdqfsuznniqsa7gp3xyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run swartype/sdxl-pixar using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "swartype/sdxl-pixar:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", { input: { width: 1024, height: 1024, prompt: "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run swartype/sdxl-pixar using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "swartype/sdxl-pixar:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", input={ "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run swartype/sdxl-pixar 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": "81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run swartype/sdxl-pixar using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/swartype/sdxl-pixar@sha256:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048 \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background"' \ -i 'refine="no_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.6' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=true' \ -i 'high_noise_frac=0.8' \ -i 'negative_prompt="noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Pull and run swartype/sdxl-pixar using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/swartype/sdxl-pixar@sha256:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2023-10-21T12:01:30.620293Z", "created_at": "2023-10-21T12:00:42.604542Z", "data_removed": false, "error": null, "id": "v2qfjotbdqfsuznniqsa7gp3xy", "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 23837\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.69it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.69it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.70it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.70it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.69it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.69it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.69it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.69it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.69it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.69it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.68it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.68it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.68it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.68it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.68it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.68it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.68it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.68it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.67it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.68it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.68it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.68it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.68it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.68it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.68it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.68it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.68it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.68it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.68it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.68it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.68it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.67it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.68it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.68it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.68it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.67it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.68it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.67it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.67it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.67it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.67it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.67it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.67it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.68it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.67it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.67it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.68it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.68it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.68it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.68it/s]", "metrics": { "predict_time": 16.86681, "total_time": 48.015751 }, "output": [ "https://replicate.delivery/pbxt/13Q5JVKgzHJqPJ799PA7njhP2qULHFbDqylftjJU04TNfWwRA/out-0.png" ], "started_at": "2023-10-21T12:01:13.753483Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/v2qfjotbdqfsuznniqsa7gp3xy", "cancel": "https://api.replicate.com/v1/predictions/v2qfjotbdqfsuznniqsa7gp3xy/cancel" }, "version": "81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048" }
Generated inUsing seed: 23837 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.69it/s] 4%|▍ | 2/50 [00:00<00:13, 3.69it/s] 6%|▌ | 3/50 [00:00<00:12, 3.70it/s] 8%|▊ | 4/50 [00:01<00:12, 3.70it/s] 10%|█ | 5/50 [00:01<00:12, 3.69it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.69it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.69it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.69it/s] 20%|██ | 10/50 [00:02<00:10, 3.69it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.69it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.68it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.68it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.68it/s] 30%|███ | 15/50 [00:04<00:09, 3.68it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.68it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.68it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.68it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.68it/s] 40%|████ | 20/50 [00:05<00:08, 3.67it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.68it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.68it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.68it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.68it/s] 50%|█████ | 25/50 [00:06<00:06, 3.68it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.68it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.68it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.68it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.68it/s] 60%|██████ | 30/50 [00:08<00:05, 3.68it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.68it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.68it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.67it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.68it/s] 70%|███████ | 35/50 [00:09<00:04, 3.68it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.68it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.67it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.68it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.67it/s] 80%|████████ | 40/50 [00:10<00:02, 3.67it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.67it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.67it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.67it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.67it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.68it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.67it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.67it/s] 96%|█████████▌| 48/50 [00:13<00:00, 3.68it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.68it/s] 100%|██████████| 50/50 [00:13<00:00, 3.68it/s] 100%|██████████| 50/50 [00:13<00:00, 3.68it/s]
Prediction
swartype/sdxl-pixar:81f8bbd3IDzbnn643bw7ziyddufo3mvl7v2qStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- breathtaking 3D animated movie poster in the style of Pixar with Elon Musk at the center and galaxy space in the background
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo,
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with Elon Musk at the center and galaxy space in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo,", "prompt_strength": 0.8, "num_inference_steps": 50 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run swartype/sdxl-pixar using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "swartype/sdxl-pixar:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", { input: { width: 1024, height: 1024, prompt: "breathtaking 3D animated movie poster in the style of Pixar with Elon Musk at the center and galaxy space in the background", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo,", prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run swartype/sdxl-pixar using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "swartype/sdxl-pixar:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", input={ "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with Elon Musk at the center and galaxy space in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo,", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run swartype/sdxl-pixar 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": "81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with Elon Musk at the center and galaxy space in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo,", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run swartype/sdxl-pixar using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/swartype/sdxl-pixar@sha256:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048 \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="breathtaking 3D animated movie poster in the style of Pixar with Elon Musk at the center and galaxy space in the background"' \ -i 'refine="no_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.6' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=true' \ -i 'high_noise_frac=0.8' \ -i 'negative_prompt="noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo,"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Pull and run swartype/sdxl-pixar using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/swartype/sdxl-pixar@sha256:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with Elon Musk at the center and galaxy space in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo,", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2023-10-21T11:48:35.265575Z", "created_at": "2023-10-21T11:48:05.889525Z", "data_removed": false, "error": null, "id": "zbnn643bw7ziyddufo3mvl7v2q", "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with Elon Musk at the center and galaxy space in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo,", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 38792\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: breathtaking 3D animated movie poster in the style of Pixar with Elon Musk at the center and galaxy space in the background\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.69it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.67it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.67it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.67it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.67it/s]\n 12%|█▏ | 6/50 [00:01<00:12, 3.66it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.67it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.67it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.67it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.66it/s]\n 22%|██▏ | 11/50 [00:03<00:10, 3.66it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.66it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.66it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.66it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.66it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.66it/s]\n 34%|███▍ | 17/50 [00:04<00:09, 3.66it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.66it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.66it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.66it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.66it/s]\n 44%|████▍ | 22/50 [00:06<00:07, 3.66it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.66it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.66it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.66it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.66it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.66it/s]\n 56%|█████▌ | 28/50 [00:07<00:06, 3.66it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.66it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.66it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.66it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.66it/s]\n 66%|██████▌ | 33/50 [00:09<00:04, 3.66it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.66it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.66it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.65it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.66it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.66it/s]\n 78%|███████▊ | 39/50 [00:10<00:03, 3.65it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.66it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.66it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.65it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.66it/s]\n 88%|████████▊ | 44/50 [00:12<00:01, 3.65it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.65it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.65it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.65it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.65it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.65it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.65it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.66it/s]", "metrics": { "predict_time": 17.997166, "total_time": 29.37605 }, "output": [ "https://replicate.delivery/pbxt/E2Fbts3xmHYwJtAeO9fCfiygkyrc2JTtpPsqbkRyYkTlktgjA/out-0.png" ], "started_at": "2023-10-21T11:48:17.268409Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/zbnn643bw7ziyddufo3mvl7v2q", "cancel": "https://api.replicate.com/v1/predictions/zbnn643bw7ziyddufo3mvl7v2q/cancel" }, "version": "81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048" }
Generated inUsing seed: 38792 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: breathtaking 3D animated movie poster in the style of Pixar with Elon Musk at the center and galaxy space in the background txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.69it/s] 4%|▍ | 2/50 [00:00<00:13, 3.67it/s] 6%|▌ | 3/50 [00:00<00:12, 3.67it/s] 8%|▊ | 4/50 [00:01<00:12, 3.67it/s] 10%|█ | 5/50 [00:01<00:12, 3.67it/s] 12%|█▏ | 6/50 [00:01<00:12, 3.66it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.67it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.67it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.67it/s] 20%|██ | 10/50 [00:02<00:10, 3.66it/s] 22%|██▏ | 11/50 [00:03<00:10, 3.66it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.66it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.66it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.66it/s] 30%|███ | 15/50 [00:04<00:09, 3.66it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.66it/s] 34%|███▍ | 17/50 [00:04<00:09, 3.66it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.66it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.66it/s] 40%|████ | 20/50 [00:05<00:08, 3.66it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.66it/s] 44%|████▍ | 22/50 [00:06<00:07, 3.66it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.66it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.66it/s] 50%|█████ | 25/50 [00:06<00:06, 3.66it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.66it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.66it/s] 56%|█████▌ | 28/50 [00:07<00:06, 3.66it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.66it/s] 60%|██████ | 30/50 [00:08<00:05, 3.66it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.66it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.66it/s] 66%|██████▌ | 33/50 [00:09<00:04, 3.66it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.66it/s] 70%|███████ | 35/50 [00:09<00:04, 3.66it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.65it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.66it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.66it/s] 78%|███████▊ | 39/50 [00:10<00:03, 3.65it/s] 80%|████████ | 40/50 [00:10<00:02, 3.66it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.66it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.65it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.66it/s] 88%|████████▊ | 44/50 [00:12<00:01, 3.65it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.65it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.65it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.65it/s] 96%|█████████▌| 48/50 [00:13<00:00, 3.65it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.65it/s] 100%|██████████| 50/50 [00:13<00:00, 3.65it/s] 100%|██████████| 50/50 [00:13<00:00, 3.66it/s]
Prediction
swartype/sdxl-pixar:81f8bbd3IDa6zfwmdbnuzfewqfmp26hs35ouStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a mexico carnival in the background
- refine
- no_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
- 50
{ "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a mexico carnival in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run swartype/sdxl-pixar using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "swartype/sdxl-pixar:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", { input: { width: 1024, height: 1024, prompt: "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a mexico carnival in the background", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "", prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run swartype/sdxl-pixar using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "swartype/sdxl-pixar:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", input={ "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a mexico carnival in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run swartype/sdxl-pixar 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": "81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a mexico carnival in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run swartype/sdxl-pixar using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/swartype/sdxl-pixar@sha256:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048 \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a mexico carnival in the background"' \ -i 'refine="no_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.6' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=true' \ -i 'high_noise_frac=0.8' \ -i 'negative_prompt=""' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Pull and run swartype/sdxl-pixar using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/swartype/sdxl-pixar@sha256:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a mexico carnival in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2023-10-21T11:45:10.387448Z", "created_at": "2023-10-21T11:44:48.043100Z", "data_removed": false, "error": null, "id": "a6zfwmdbnuzfewqfmp26hs35ou", "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a mexico carnival in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 26463\nEnsuring enough disk space...\nFree disk space: 1719139905536\nDownloading weights: https://pbxt.replicate.delivery/J1q6LulfioyaM6jmrFPoDH8UtucBitfbZk2cqpp6rD6PFWwRA/trained_model.tar\nb'Downloaded 186 MB bytes in 0.567s (328 MB/s)\\nExtracted 186 MB in 0.081s (2.3 GB/s)\\n'\nDownloaded weights in 1.009598731994629 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a mexico carnival in the background\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.70it/s]\n 4%|▍ | 2/50 [00:00<00:12, 3.70it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.70it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.70it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.70it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.70it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.69it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.69it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.69it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.68it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.68it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.68it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.68it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.68it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.68it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.68it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.68it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.68it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.68it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.68it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.68it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.68it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.68it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.67it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.67it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.67it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.67it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.67it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.67it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.67it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.68it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.68it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.67it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.67it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.67it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.67it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.67it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.67it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.68it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.67it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.67it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.67it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.67it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.67it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.67it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.66it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.67it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.67it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.67it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.68it/s]", "metrics": { "predict_time": 18.049393, "total_time": 22.344348 }, "output": [ "https://replicate.delivery/pbxt/fTmmiAjjGBwpHyFYD7pXDPtIaY68qcDmCCTofgtl1rAFvWwRA/out-0.png" ], "started_at": "2023-10-21T11:44:52.338055Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/a6zfwmdbnuzfewqfmp26hs35ou", "cancel": "https://api.replicate.com/v1/predictions/a6zfwmdbnuzfewqfmp26hs35ou/cancel" }, "version": "81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048" }
Generated inUsing seed: 26463 Ensuring enough disk space... Free disk space: 1719139905536 Downloading weights: https://pbxt.replicate.delivery/J1q6LulfioyaM6jmrFPoDH8UtucBitfbZk2cqpp6rD6PFWwRA/trained_model.tar b'Downloaded 186 MB bytes in 0.567s (328 MB/s)\nExtracted 186 MB in 0.081s (2.3 GB/s)\n' Downloaded weights in 1.009598731994629 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a mexico carnival in the background txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.70it/s] 4%|▍ | 2/50 [00:00<00:12, 3.70it/s] 6%|▌ | 3/50 [00:00<00:12, 3.70it/s] 8%|▊ | 4/50 [00:01<00:12, 3.70it/s] 10%|█ | 5/50 [00:01<00:12, 3.70it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.70it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.69it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.69it/s] 20%|██ | 10/50 [00:02<00:10, 3.69it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.68it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.68it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.68it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.68it/s] 30%|███ | 15/50 [00:04<00:09, 3.68it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.68it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.68it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.68it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.68it/s] 40%|████ | 20/50 [00:05<00:08, 3.68it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.68it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.68it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.68it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.68it/s] 50%|█████ | 25/50 [00:06<00:06, 3.67it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.67it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.67it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.67it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.67it/s] 60%|██████ | 30/50 [00:08<00:05, 3.67it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.67it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.68it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.68it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.67it/s] 70%|███████ | 35/50 [00:09<00:04, 3.67it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.67it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.67it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.67it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.67it/s] 80%|████████ | 40/50 [00:10<00:02, 3.68it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.67it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.67it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.67it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.67it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.67it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.67it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.66it/s] 96%|█████████▌| 48/50 [00:13<00:00, 3.67it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.67it/s] 100%|██████████| 50/50 [00:13<00:00, 3.67it/s] 100%|██████████| 50/50 [00:13<00:00, 3.68it/s]
Prediction
swartype/sdxl-pixar:81f8bbd3ID43vaollbk6e43idxnbdeg7543iStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- breathtaking 3D animated movie poster in the style of Pixar with thomas shelby peaky blinders at the center and 1920 city in the background
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with thomas shelby peaky blinders at the center and 1920 city in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run swartype/sdxl-pixar using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "swartype/sdxl-pixar:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", { input: { width: 1024, height: 1024, prompt: "breathtaking 3D animated movie poster in the style of Pixar with thomas shelby peaky blinders at the center and 1920 city in the background", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run swartype/sdxl-pixar using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "swartype/sdxl-pixar:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", input={ "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with thomas shelby peaky blinders at the center and 1920 city in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run swartype/sdxl-pixar 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": "81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with thomas shelby peaky blinders at the center and 1920 city in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run swartype/sdxl-pixar using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/swartype/sdxl-pixar@sha256:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048 \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="breathtaking 3D animated movie poster in the style of Pixar with thomas shelby peaky blinders at the center and 1920 city in the background"' \ -i 'refine="no_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.6' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=true' \ -i 'high_noise_frac=0.8' \ -i 'negative_prompt="noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Pull and run swartype/sdxl-pixar using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/swartype/sdxl-pixar@sha256:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with thomas shelby peaky blinders at the center and 1920 city in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2023-10-21T13:20:11.417522Z", "created_at": "2023-10-21T13:19:52.364569Z", "data_removed": false, "error": null, "id": "43vaollbk6e43idxnbdeg7543i", "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with thomas shelby peaky blinders at the center and 1920 city in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 5807\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: breathtaking 3D animated movie poster in the style of Pixar with thomas shelby peaky blinders at the center and 1920 city in the background\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.68it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.66it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.66it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.65it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.65it/s]\n 12%|█▏ | 6/50 [00:01<00:12, 3.65it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.65it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.65it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.64it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.65it/s]\n 22%|██▏ | 11/50 [00:03<00:10, 3.65it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.66it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.66it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.66it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.65it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.65it/s]\n 34%|███▍ | 17/50 [00:04<00:09, 3.65it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.65it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.65it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.65it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.66it/s]\n 44%|████▍ | 22/50 [00:06<00:07, 3.66it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.65it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.65it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.65it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.65it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.65it/s]\n 56%|█████▌ | 28/50 [00:07<00:06, 3.65it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.65it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.65it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.65it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.65it/s]\n 66%|██████▌ | 33/50 [00:09<00:04, 3.65it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.65it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.65it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.65it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.65it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.65it/s]\n 78%|███████▊ | 39/50 [00:10<00:03, 3.65it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.65it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.64it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.60it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.61it/s]\n 88%|████████▊ | 44/50 [00:12<00:01, 3.62it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.63it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.63it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.64it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.64it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.64it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.64it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.65it/s]", "metrics": { "predict_time": 17.758961, "total_time": 19.052953 }, "output": [ "https://replicate.delivery/pbxt/bRTyhUHOKSr0GJnfG8M6ilvQgSK5WEOl5cjxBxiljrbFEM4IA/out-0.png" ], "started_at": "2023-10-21T13:19:53.658561Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/43vaollbk6e43idxnbdeg7543i", "cancel": "https://api.replicate.com/v1/predictions/43vaollbk6e43idxnbdeg7543i/cancel" }, "version": "81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048" }
Generated inUsing seed: 5807 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: breathtaking 3D animated movie poster in the style of Pixar with thomas shelby peaky blinders at the center and 1920 city in the background txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.68it/s] 4%|▍ | 2/50 [00:00<00:13, 3.66it/s] 6%|▌ | 3/50 [00:00<00:12, 3.66it/s] 8%|▊ | 4/50 [00:01<00:12, 3.65it/s] 10%|█ | 5/50 [00:01<00:12, 3.65it/s] 12%|█▏ | 6/50 [00:01<00:12, 3.65it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.65it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.65it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.64it/s] 20%|██ | 10/50 [00:02<00:10, 3.65it/s] 22%|██▏ | 11/50 [00:03<00:10, 3.65it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.66it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.66it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.66it/s] 30%|███ | 15/50 [00:04<00:09, 3.65it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.65it/s] 34%|███▍ | 17/50 [00:04<00:09, 3.65it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.65it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.65it/s] 40%|████ | 20/50 [00:05<00:08, 3.65it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.66it/s] 44%|████▍ | 22/50 [00:06<00:07, 3.66it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.65it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.65it/s] 50%|█████ | 25/50 [00:06<00:06, 3.65it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.65it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.65it/s] 56%|█████▌ | 28/50 [00:07<00:06, 3.65it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.65it/s] 60%|██████ | 30/50 [00:08<00:05, 3.65it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.65it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.65it/s] 66%|██████▌ | 33/50 [00:09<00:04, 3.65it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.65it/s] 70%|███████ | 35/50 [00:09<00:04, 3.65it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.65it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.65it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.65it/s] 78%|███████▊ | 39/50 [00:10<00:03, 3.65it/s] 80%|████████ | 40/50 [00:10<00:02, 3.65it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.64it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.60it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.61it/s] 88%|████████▊ | 44/50 [00:12<00:01, 3.62it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.63it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.63it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.64it/s] 96%|█████████▌| 48/50 [00:13<00:00, 3.64it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.64it/s] 100%|██████████| 50/50 [00:13<00:00, 3.64it/s] 100%|██████████| 50/50 [00:13<00:00, 3.65it/s]
Prediction
swartype/sdxl-pixar:81f8bbd3IDtrx4wotb6fgnflo3b22diykj4yStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 4
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run swartype/sdxl-pixar using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "swartype/sdxl-pixar:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", { input: { width: 1024, height: 1024, prompt: "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 4, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run swartype/sdxl-pixar using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "swartype/sdxl-pixar:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", input={ "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run swartype/sdxl-pixar 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": "81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run swartype/sdxl-pixar using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/swartype/sdxl-pixar@sha256:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048 \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background"' \ -i 'refine="no_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.6' \ -i 'num_outputs=4' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=true' \ -i 'high_noise_frac=0.8' \ -i 'negative_prompt="noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Pull and run swartype/sdxl-pixar using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/swartype/sdxl-pixar@sha256:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2023-10-21T14:05:48.551386Z", "created_at": "2023-10-21T14:04:44.166307Z", "data_removed": false, "error": null, "id": "trx4wotb6fgnflo3b22diykj4y", "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 27651\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:01<00:51, 1.04s/it]\n 4%|▍ | 2/50 [00:02<00:50, 1.05s/it]\n 6%|▌ | 3/50 [00:03<00:49, 1.05s/it]\n 8%|▊ | 4/50 [00:04<00:48, 1.05s/it]\n 10%|█ | 5/50 [00:05<00:47, 1.05s/it]\n 12%|█▏ | 6/50 [00:06<00:46, 1.05s/it]\n 14%|█▍ | 7/50 [00:07<00:45, 1.05s/it]\n 16%|█▌ | 8/50 [00:08<00:44, 1.05s/it]\n 18%|█▊ | 9/50 [00:09<00:43, 1.05s/it]\n 20%|██ | 10/50 [00:10<00:42, 1.05s/it]\n 22%|██▏ | 11/50 [00:11<00:41, 1.05s/it]\n 24%|██▍ | 12/50 [00:12<00:39, 1.05s/it]\n 26%|██▌ | 13/50 [00:13<00:38, 1.05s/it]\n 28%|██▊ | 14/50 [00:14<00:37, 1.05s/it]\n 30%|███ | 15/50 [00:15<00:36, 1.05s/it]\n 32%|███▏ | 16/50 [00:16<00:35, 1.05s/it]\n 34%|███▍ | 17/50 [00:17<00:34, 1.05s/it]\n 36%|███▌ | 18/50 [00:18<00:33, 1.05s/it]\n 38%|███▊ | 19/50 [00:19<00:32, 1.05s/it]\n 40%|████ | 20/50 [00:21<00:31, 1.06s/it]\n 42%|████▏ | 21/50 [00:22<00:30, 1.06s/it]\n 44%|████▍ | 22/50 [00:23<00:29, 1.06s/it]\n 46%|████▌ | 23/50 [00:24<00:28, 1.06s/it]\n 48%|████▊ | 24/50 [00:25<00:27, 1.06s/it]\n 50%|█████ | 25/50 [00:26<00:26, 1.06s/it]\n 52%|█████▏ | 26/50 [00:27<00:25, 1.06s/it]\n 54%|█████▍ | 27/50 [00:28<00:24, 1.06s/it]\n 56%|█████▌ | 28/50 [00:29<00:23, 1.06s/it]\n 58%|█████▊ | 29/50 [00:30<00:22, 1.06s/it]\n 60%|██████ | 30/50 [00:31<00:21, 1.06s/it]\n 62%|██████▏ | 31/50 [00:32<00:20, 1.06s/it]\n 64%|██████▍ | 32/50 [00:33<00:19, 1.06s/it]\n 66%|██████▌ | 33/50 [00:34<00:17, 1.06s/it]\n 68%|██████▊ | 34/50 [00:35<00:16, 1.06s/it]\n 70%|███████ | 35/50 [00:36<00:15, 1.06s/it]\n 72%|███████▏ | 36/50 [00:37<00:14, 1.06s/it]\n 74%|███████▍ | 37/50 [00:39<00:13, 1.06s/it]\n 76%|███████▌ | 38/50 [00:40<00:12, 1.06s/it]\n 78%|███████▊ | 39/50 [00:41<00:11, 1.06s/it]\n 80%|████████ | 40/50 [00:42<00:10, 1.06s/it]\n 82%|████████▏ | 41/50 [00:43<00:09, 1.06s/it]\n 84%|████████▍ | 42/50 [00:44<00:08, 1.06s/it]\n 86%|████████▌ | 43/50 [00:45<00:07, 1.06s/it]\n 88%|████████▊ | 44/50 [00:46<00:06, 1.06s/it]\n 90%|█████████ | 45/50 [00:47<00:05, 1.06s/it]\n 92%|█████████▏| 46/50 [00:48<00:04, 1.06s/it]\n 94%|█████████▍| 47/50 [00:49<00:03, 1.06s/it]\n 96%|█████████▌| 48/50 [00:50<00:02, 1.06s/it]\n 98%|█████████▊| 49/50 [00:51<00:01, 1.06s/it]\n100%|██████████| 50/50 [00:52<00:00, 1.06s/it]\n100%|██████████| 50/50 [00:52<00:00, 1.06s/it]", "metrics": { "predict_time": 63.150545, "total_time": 64.385079 }, "output": [ "https://replicate.delivery/pbxt/jXrwfXs93b30CqrCRce43Wl8aKJZsMfbTqNeG9Tff5AauMGcE/out-0.png", "https://replicate.delivery/pbxt/ie1zH7Y9NvwPICuaXYIjpdwwIEb1IBhuRtx825ldfFe0lxgjA/out-1.png", "https://replicate.delivery/pbxt/AN43AqrstnqeBaqrTgl9AIlZ63HbXEsYyRfQZEBeC9T3lxgjA/out-2.png", "https://replicate.delivery/pbxt/59dtvceIVDXVYafsBEpeKXrTpfS6Sff9AYJGFKodVaaOvMGcE/out-3.png" ], "started_at": "2023-10-21T14:04:45.400841Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/trx4wotb6fgnflo3b22diykj4y", "cancel": "https://api.replicate.com/v1/predictions/trx4wotb6fgnflo3b22diykj4y/cancel" }, "version": "81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048" }
Generated inUsing seed: 27651 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: breathtaking 3D animated movie poster in the style of Pixar with a man at the center and forest in the background txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:01<00:51, 1.04s/it] 4%|▍ | 2/50 [00:02<00:50, 1.05s/it] 6%|▌ | 3/50 [00:03<00:49, 1.05s/it] 8%|▊ | 4/50 [00:04<00:48, 1.05s/it] 10%|█ | 5/50 [00:05<00:47, 1.05s/it] 12%|█▏ | 6/50 [00:06<00:46, 1.05s/it] 14%|█▍ | 7/50 [00:07<00:45, 1.05s/it] 16%|█▌ | 8/50 [00:08<00:44, 1.05s/it] 18%|█▊ | 9/50 [00:09<00:43, 1.05s/it] 20%|██ | 10/50 [00:10<00:42, 1.05s/it] 22%|██▏ | 11/50 [00:11<00:41, 1.05s/it] 24%|██▍ | 12/50 [00:12<00:39, 1.05s/it] 26%|██▌ | 13/50 [00:13<00:38, 1.05s/it] 28%|██▊ | 14/50 [00:14<00:37, 1.05s/it] 30%|███ | 15/50 [00:15<00:36, 1.05s/it] 32%|███▏ | 16/50 [00:16<00:35, 1.05s/it] 34%|███▍ | 17/50 [00:17<00:34, 1.05s/it] 36%|███▌ | 18/50 [00:18<00:33, 1.05s/it] 38%|███▊ | 19/50 [00:19<00:32, 1.05s/it] 40%|████ | 20/50 [00:21<00:31, 1.06s/it] 42%|████▏ | 21/50 [00:22<00:30, 1.06s/it] 44%|████▍ | 22/50 [00:23<00:29, 1.06s/it] 46%|████▌ | 23/50 [00:24<00:28, 1.06s/it] 48%|████▊ | 24/50 [00:25<00:27, 1.06s/it] 50%|█████ | 25/50 [00:26<00:26, 1.06s/it] 52%|█████▏ | 26/50 [00:27<00:25, 1.06s/it] 54%|█████▍ | 27/50 [00:28<00:24, 1.06s/it] 56%|█████▌ | 28/50 [00:29<00:23, 1.06s/it] 58%|█████▊ | 29/50 [00:30<00:22, 1.06s/it] 60%|██████ | 30/50 [00:31<00:21, 1.06s/it] 62%|██████▏ | 31/50 [00:32<00:20, 1.06s/it] 64%|██████▍ | 32/50 [00:33<00:19, 1.06s/it] 66%|██████▌ | 33/50 [00:34<00:17, 1.06s/it] 68%|██████▊ | 34/50 [00:35<00:16, 1.06s/it] 70%|███████ | 35/50 [00:36<00:15, 1.06s/it] 72%|███████▏ | 36/50 [00:37<00:14, 1.06s/it] 74%|███████▍ | 37/50 [00:39<00:13, 1.06s/it] 76%|███████▌ | 38/50 [00:40<00:12, 1.06s/it] 78%|███████▊ | 39/50 [00:41<00:11, 1.06s/it] 80%|████████ | 40/50 [00:42<00:10, 1.06s/it] 82%|████████▏ | 41/50 [00:43<00:09, 1.06s/it] 84%|████████▍ | 42/50 [00:44<00:08, 1.06s/it] 86%|████████▌ | 43/50 [00:45<00:07, 1.06s/it] 88%|████████▊ | 44/50 [00:46<00:06, 1.06s/it] 90%|█████████ | 45/50 [00:47<00:05, 1.06s/it] 92%|█████████▏| 46/50 [00:48<00:04, 1.06s/it] 94%|█████████▍| 47/50 [00:49<00:03, 1.06s/it] 96%|█████████▌| 48/50 [00:50<00:02, 1.06s/it] 98%|█████████▊| 49/50 [00:51<00:01, 1.06s/it] 100%|██████████| 50/50 [00:52<00:00, 1.06s/it] 100%|██████████| 50/50 [00:52<00:00, 1.06s/it]
Prediction
swartype/sdxl-pixar:81f8bbd3IDekgonptbzk3zkoe5z2la54qmgaStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedby @swartypeInput
- width
- 1024
- height
- 1024
- prompt
- breathtaking 3D animated movie poster in the style of Pixar with superman at the center and a destroyed city in the background
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with superman at the center and a destroyed city in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run swartype/sdxl-pixar using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "swartype/sdxl-pixar:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", { input: { width: 1024, height: 1024, prompt: "breathtaking 3D animated movie poster in the style of Pixar with superman at the center and a destroyed city in the background", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run swartype/sdxl-pixar using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "swartype/sdxl-pixar:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", input={ "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with superman at the center and a destroyed city in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run swartype/sdxl-pixar 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": "81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with superman at the center and a destroyed city in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run swartype/sdxl-pixar using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/swartype/sdxl-pixar@sha256:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048 \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="breathtaking 3D animated movie poster in the style of Pixar with superman at the center and a destroyed city in the background"' \ -i 'refine="no_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.6' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=true' \ -i 'high_noise_frac=0.8' \ -i 'negative_prompt="noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Pull and run swartype/sdxl-pixar using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/swartype/sdxl-pixar@sha256:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with superman at the center and a destroyed city in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2023-10-22T10:33:18.715005Z", "created_at": "2023-10-22T10:32:47.919870Z", "data_removed": false, "error": null, "id": "ekgonptbzk3zkoe5z2la54qmga", "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with superman at the center and a destroyed city in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 15124\nEnsuring enough disk space...\nFree disk space: 1763095707648\nDownloading weights: https://pbxt.replicate.delivery/J1q6LulfioyaM6jmrFPoDH8UtucBitfbZk2cqpp6rD6PFWwRA/trained_model.tar\nb'Downloaded 186 MB bytes in 11.867s (16 MB/s)\\nExtracted 186 MB in 0.079s (2.3 GB/s)\\n'\nDownloaded weights in 12.45238733291626 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: breathtaking 3D animated movie poster in the style of Pixar with superman at the center and a destroyed city in the background\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.68it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.67it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.66it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.65it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.65it/s]\n 12%|█▏ | 6/50 [00:01<00:12, 3.65it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.65it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.64it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.64it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.64it/s]\n 22%|██▏ | 11/50 [00:03<00:10, 3.64it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.64it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.64it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.64it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.64it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.64it/s]\n 34%|███▍ | 17/50 [00:04<00:09, 3.64it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.64it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.64it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.63it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.64it/s]\n 44%|████▍ | 22/50 [00:06<00:07, 3.64it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.64it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.64it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.63it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.63it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.63it/s]\n 56%|█████▌ | 28/50 [00:07<00:06, 3.64it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.63it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.63it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.63it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.63it/s]\n 66%|██████▌ | 33/50 [00:09<00:04, 3.63it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.63it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.63it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.63it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.63it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.63it/s]\n 78%|███████▊ | 39/50 [00:10<00:03, 3.63it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.63it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.63it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.63it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.63it/s]\n 88%|████████▊ | 44/50 [00:12<00:01, 3.63it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.63it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.63it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.63it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.63it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.63it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.63it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.64it/s]", "metrics": { "predict_time": 29.29581, "total_time": 30.795135 }, "output": [ "https://replicate.delivery/pbxt/p2zBSSZ7IT4AHR381vy23z6IRAOfr43sf2j6bXIsYuZuxqwRA/out-0.png" ], "started_at": "2023-10-22T10:32:49.419195Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ekgonptbzk3zkoe5z2la54qmga", "cancel": "https://api.replicate.com/v1/predictions/ekgonptbzk3zkoe5z2la54qmga/cancel" }, "version": "81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048" }
Generated inUsing seed: 15124 Ensuring enough disk space... Free disk space: 1763095707648 Downloading weights: https://pbxt.replicate.delivery/J1q6LulfioyaM6jmrFPoDH8UtucBitfbZk2cqpp6rD6PFWwRA/trained_model.tar b'Downloaded 186 MB bytes in 11.867s (16 MB/s)\nExtracted 186 MB in 0.079s (2.3 GB/s)\n' Downloaded weights in 12.45238733291626 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: breathtaking 3D animated movie poster in the style of Pixar with superman at the center and a destroyed city in the background txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.68it/s] 4%|▍ | 2/50 [00:00<00:13, 3.67it/s] 6%|▌ | 3/50 [00:00<00:12, 3.66it/s] 8%|▊ | 4/50 [00:01<00:12, 3.65it/s] 10%|█ | 5/50 [00:01<00:12, 3.65it/s] 12%|█▏ | 6/50 [00:01<00:12, 3.65it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.65it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.64it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.64it/s] 20%|██ | 10/50 [00:02<00:10, 3.64it/s] 22%|██▏ | 11/50 [00:03<00:10, 3.64it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.64it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.64it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.64it/s] 30%|███ | 15/50 [00:04<00:09, 3.64it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.64it/s] 34%|███▍ | 17/50 [00:04<00:09, 3.64it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.64it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.64it/s] 40%|████ | 20/50 [00:05<00:08, 3.63it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.64it/s] 44%|████▍ | 22/50 [00:06<00:07, 3.64it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.64it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.64it/s] 50%|█████ | 25/50 [00:06<00:06, 3.63it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.63it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.63it/s] 56%|█████▌ | 28/50 [00:07<00:06, 3.64it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.63it/s] 60%|██████ | 30/50 [00:08<00:05, 3.63it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.63it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.63it/s] 66%|██████▌ | 33/50 [00:09<00:04, 3.63it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.63it/s] 70%|███████ | 35/50 [00:09<00:04, 3.63it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.63it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.63it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.63it/s] 78%|███████▊ | 39/50 [00:10<00:03, 3.63it/s] 80%|████████ | 40/50 [00:10<00:02, 3.63it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.63it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.63it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.63it/s] 88%|████████▊ | 44/50 [00:12<00:01, 3.63it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.63it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.63it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.63it/s] 96%|█████████▌| 48/50 [00:13<00:00, 3.63it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.63it/s] 100%|██████████| 50/50 [00:13<00:00, 3.63it/s] 100%|██████████| 50/50 [00:13<00:00, 3.64it/s]
Prediction
swartype/sdxl-pixar:81f8bbd3ID45rouc3b6wyqj3zviip2jgmcxeStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a volcano in the background
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a volcano in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run swartype/sdxl-pixar using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "swartype/sdxl-pixar:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", { input: { width: 1024, height: 1024, prompt: "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a volcano in the background", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run swartype/sdxl-pixar using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "swartype/sdxl-pixar:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", input={ "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a volcano in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run swartype/sdxl-pixar 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": "81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048", "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a volcano in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run swartype/sdxl-pixar using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/swartype/sdxl-pixar@sha256:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048 \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a volcano in the background"' \ -i 'refine="no_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.6' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=true' \ -i 'high_noise_frac=0.8' \ -i 'negative_prompt="noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Pull and run swartype/sdxl-pixar using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/swartype/sdxl-pixar@sha256:81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a volcano in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2023-10-28T17:07:41.191294Z", "created_at": "2023-10-28T17:07:24.412876Z", "data_removed": false, "error": null, "id": "45rouc3b6wyqj3zviip2jgmcxe", "input": { "width": 1024, "height": 1024, "prompt": "breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a volcano in the background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "noisy, sloppy, messy, grainy, highly detailed, ultra textured, photo, NSFW", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 31497\nskipping loading .. weights already loaded\nPrompt: breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a volcano in the background\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:14, 3.46it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.45it/s]\n 6%|▌ | 3/50 [00:00<00:13, 3.44it/s]\n 8%|▊ | 4/50 [00:01<00:13, 3.44it/s]\n 10%|█ | 5/50 [00:01<00:13, 3.43it/s]\n 12%|█▏ | 6/50 [00:01<00:12, 3.43it/s]\n 14%|█▍ | 7/50 [00:02<00:12, 3.43it/s]\n 16%|█▌ | 8/50 [00:02<00:12, 3.42it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.42it/s]\n 20%|██ | 10/50 [00:02<00:11, 3.42it/s]\n 22%|██▏ | 11/50 [00:03<00:11, 3.42it/s]\n 24%|██▍ | 12/50 [00:03<00:11, 3.42it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.42it/s]\n 28%|██▊ | 14/50 [00:04<00:10, 3.42it/s]\n 30%|███ | 15/50 [00:04<00:10, 3.42it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.41it/s]\n 34%|███▍ | 17/50 [00:04<00:09, 3.42it/s]\n 36%|███▌ | 18/50 [00:05<00:09, 3.42it/s]\n 38%|███▊ | 19/50 [00:05<00:09, 3.42it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.42it/s]\n 42%|████▏ | 21/50 [00:06<00:08, 3.41it/s]\n 44%|████▍ | 22/50 [00:06<00:08, 3.41it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.42it/s]\n 48%|████▊ | 24/50 [00:07<00:07, 3.42it/s]\n 50%|█████ | 25/50 [00:07<00:07, 3.41it/s]\n 52%|█████▏ | 26/50 [00:07<00:07, 3.41it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.41it/s]\n 56%|█████▌ | 28/50 [00:08<00:06, 3.40it/s]\n 58%|█████▊ | 29/50 [00:08<00:06, 3.41it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.41it/s]\n 62%|██████▏ | 31/50 [00:09<00:05, 3.41it/s]\n 64%|██████▍ | 32/50 [00:09<00:05, 3.41it/s]\n 66%|██████▌ | 33/50 [00:09<00:04, 3.41it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.41it/s]\n 70%|███████ | 35/50 [00:10<00:04, 3.41it/s]\n 72%|███████▏ | 36/50 [00:10<00:04, 3.41it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.41it/s]\n 76%|███████▌ | 38/50 [00:11<00:03, 3.41it/s]\n 78%|███████▊ | 39/50 [00:11<00:03, 3.41it/s]\n 80%|████████ | 40/50 [00:11<00:02, 3.41it/s]\n 82%|████████▏ | 41/50 [00:12<00:02, 3.40it/s]\n 84%|████████▍ | 42/50 [00:12<00:02, 3.41it/s]\n 86%|████████▌ | 43/50 [00:12<00:02, 3.41it/s]\n 88%|████████▊ | 44/50 [00:12<00:01, 3.40it/s]\n 90%|█████████ | 45/50 [00:13<00:01, 3.41it/s]\n 92%|█████████▏| 46/50 [00:13<00:01, 3.41it/s]\n 94%|█████████▍| 47/50 [00:13<00:00, 3.40it/s]\n 96%|█████████▌| 48/50 [00:14<00:00, 3.41it/s]\n 98%|█████████▊| 49/50 [00:14<00:00, 3.41it/s]\n100%|██████████| 50/50 [00:14<00:00, 3.41it/s]\n100%|██████████| 50/50 [00:14<00:00, 3.41it/s]", "metrics": { "predict_time": 16.813811, "total_time": 16.778418 }, "output": [ "https://replicate.delivery/pbxt/bLwTAka0eeiSP0Qj3tpOfIM1EnhCfvXiNhL2sCyO1AMzd8KHB/out-0.png" ], "started_at": "2023-10-28T17:07:24.377483Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/45rouc3b6wyqj3zviip2jgmcxe", "cancel": "https://api.replicate.com/v1/predictions/45rouc3b6wyqj3zviip2jgmcxe/cancel" }, "version": "81f8bbd3463056c8521eb528feb10509cc1385e2fabef590747f159848589048" }
Generated inUsing seed: 31497 skipping loading .. weights already loaded Prompt: breathtaking 3D animated movie poster in the style of Pixar with a man at the center and a volcano in the background txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:14, 3.46it/s] 4%|▍ | 2/50 [00:00<00:13, 3.45it/s] 6%|▌ | 3/50 [00:00<00:13, 3.44it/s] 8%|▊ | 4/50 [00:01<00:13, 3.44it/s] 10%|█ | 5/50 [00:01<00:13, 3.43it/s] 12%|█▏ | 6/50 [00:01<00:12, 3.43it/s] 14%|█▍ | 7/50 [00:02<00:12, 3.43it/s] 16%|█▌ | 8/50 [00:02<00:12, 3.42it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.42it/s] 20%|██ | 10/50 [00:02<00:11, 3.42it/s] 22%|██▏ | 11/50 [00:03<00:11, 3.42it/s] 24%|██▍ | 12/50 [00:03<00:11, 3.42it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.42it/s] 28%|██▊ | 14/50 [00:04<00:10, 3.42it/s] 30%|███ | 15/50 [00:04<00:10, 3.42it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.41it/s] 34%|███▍ | 17/50 [00:04<00:09, 3.42it/s] 36%|███▌ | 18/50 [00:05<00:09, 3.42it/s] 38%|███▊ | 19/50 [00:05<00:09, 3.42it/s] 40%|████ | 20/50 [00:05<00:08, 3.42it/s] 42%|████▏ | 21/50 [00:06<00:08, 3.41it/s] 44%|████▍ | 22/50 [00:06<00:08, 3.41it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.42it/s] 48%|████▊ | 24/50 [00:07<00:07, 3.42it/s] 50%|█████ | 25/50 [00:07<00:07, 3.41it/s] 52%|█████▏ | 26/50 [00:07<00:07, 3.41it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.41it/s] 56%|█████▌ | 28/50 [00:08<00:06, 3.40it/s] 58%|█████▊ | 29/50 [00:08<00:06, 3.41it/s] 60%|██████ | 30/50 [00:08<00:05, 3.41it/s] 62%|██████▏ | 31/50 [00:09<00:05, 3.41it/s] 64%|██████▍ | 32/50 [00:09<00:05, 3.41it/s] 66%|██████▌ | 33/50 [00:09<00:04, 3.41it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.41it/s] 70%|███████ | 35/50 [00:10<00:04, 3.41it/s] 72%|███████▏ | 36/50 [00:10<00:04, 3.41it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.41it/s] 76%|███████▌ | 38/50 [00:11<00:03, 3.41it/s] 78%|███████▊ | 39/50 [00:11<00:03, 3.41it/s] 80%|████████ | 40/50 [00:11<00:02, 3.41it/s] 82%|████████▏ | 41/50 [00:12<00:02, 3.40it/s] 84%|████████▍ | 42/50 [00:12<00:02, 3.41it/s] 86%|████████▌ | 43/50 [00:12<00:02, 3.41it/s] 88%|████████▊ | 44/50 [00:12<00:01, 3.40it/s] 90%|█████████ | 45/50 [00:13<00:01, 3.41it/s] 92%|█████████▏| 46/50 [00:13<00:01, 3.41it/s] 94%|█████████▍| 47/50 [00:13<00:00, 3.40it/s] 96%|█████████▌| 48/50 [00:14<00:00, 3.41it/s] 98%|█████████▊| 49/50 [00:14<00:00, 3.41it/s] 100%|██████████| 50/50 [00:14<00:00, 3.41it/s] 100%|██████████| 50/50 [00:14<00:00, 3.41it/s]
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