codingdudecom / sdxl-mandala
SDXL model for mandalas coloring pages and coloring book designs
- Public
- 474 runs
-
L40S
- SDXL fine-tune
- License
Prediction
codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8bIDgbtx2rlbynvsbb6a4relxdluzyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- art deco TOK mandala design, big white patches, coloring pages for kids, illustration, white background, clean lines, line art
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 1
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- bad quality, ugly
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 1024, "height": 1024, "prompt": "art deco TOK mandala design, big white patches, coloring pages for kids, illustration, white background, clean lines, line art", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 1, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run codingdudecom/sdxl-mandala using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", { input: { width: 1024, height: 1024, prompt: "art deco TOK mandala design, big white patches, coloring pages for kids, illustration, white background, clean lines, line art", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 1, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.8, negative_prompt: "bad quality, ugly", prompt_strength: 0.8, num_inference_steps: 30 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun codingdudecom/sdxl-mandala using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", input={ "width": 1024, "height": 1024, "prompt": "art deco TOK mandala design, big white patches, coloring pages for kids, illustration, white background, clean lines, line art", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 1, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.8, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run codingdudecom/sdxl-mandala 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": "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", "input": { "width": 1024, "height": 1024, "prompt": "art deco TOK mandala design, big white patches, coloring pages for kids, illustration, white background, clean lines, line art", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 1, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-03-19T19:02:19.384691Z", "created_at": "2024-03-19T19:02:02.463668Z", "data_removed": false, "error": null, "id": "gbtx2rlbynvsbb6a4relxdluzy", "input": { "width": 1024, "height": 1024, "prompt": "art deco TOK mandala design, big white patches, coloring pages for kids, illustration, white background, clean lines, line art", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 1, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 12896\nEnsuring enough disk space...\nFree disk space: 2469572575232\nDownloading weights: https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar\n2024-03-19T19:02:06Z | INFO | [ Initiating ] dest=/src/weights-cache/3708132d63d38faa minimum_chunk_size=150M url=https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar\n2024-03-19T19:02:09Z | INFO | [ Complete ] dest=/src/weights-cache/3708132d63d38faa size=\"186 MB\" total_elapsed=2.113s url=https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar\nb''\nDownloaded weights in 2.2480790615081787 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: art deco <s0><s1> mandala design, big white patches, coloring pages for kids, illustration, white background, clean lines, line art\ntxt2img mode\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:07, 3.66it/s]\n 7%|▋ | 2/30 [00:00<00:07, 3.66it/s]\n 10%|█ | 3/30 [00:00<00:07, 3.66it/s]\n 13%|█▎ | 4/30 [00:01<00:07, 3.65it/s]\n 17%|█▋ | 5/30 [00:01<00:06, 3.64it/s]\n 20%|██ | 6/30 [00:01<00:06, 3.64it/s]\n 23%|██▎ | 7/30 [00:01<00:06, 3.64it/s]\n 27%|██▋ | 8/30 [00:02<00:06, 3.63it/s]\n 30%|███ | 9/30 [00:02<00:05, 3.64it/s]\n 33%|███▎ | 10/30 [00:02<00:05, 3.63it/s]\n 37%|███▋ | 11/30 [00:03<00:05, 3.63it/s]\n 40%|████ | 12/30 [00:03<00:04, 3.63it/s]\n 43%|████▎ | 13/30 [00:03<00:04, 3.63it/s]\n 47%|████▋ | 14/30 [00:03<00:04, 3.63it/s]\n 50%|█████ | 15/30 [00:04<00:04, 3.63it/s]\n 53%|█████▎ | 16/30 [00:04<00:03, 3.63it/s]\n 57%|█████▋ | 17/30 [00:04<00:03, 3.63it/s]\n 60%|██████ | 18/30 [00:04<00:03, 3.63it/s]\n 63%|██████▎ | 19/30 [00:05<00:03, 3.63it/s]\n 67%|██████▋ | 20/30 [00:05<00:02, 3.63it/s]\n 70%|███████ | 21/30 [00:05<00:02, 3.63it/s]\n 73%|███████▎ | 22/30 [00:06<00:02, 3.63it/s]\n 77%|███████▋ | 23/30 [00:06<00:01, 3.63it/s]\n 80%|████████ | 24/30 [00:06<00:01, 3.63it/s]\n 83%|████████▎ | 25/30 [00:06<00:01, 3.62it/s]\n 87%|████████▋ | 26/30 [00:07<00:01, 3.63it/s]\n 90%|█████████ | 27/30 [00:07<00:00, 3.63it/s]\n 93%|█████████▎| 28/30 [00:07<00:00, 3.62it/s]\n 97%|█████████▋| 29/30 [00:07<00:00, 3.62it/s]\n100%|██████████| 30/30 [00:08<00:00, 3.62it/s]\n100%|██████████| 30/30 [00:08<00:00, 3.63it/s]", "metrics": { "predict_time": 12.525194, "total_time": 16.921023 }, "output": [ "https://replicate.delivery/pbxt/Sb2oCT2nm2YXMhsffKbpSNHpfVAofHae3MbgZpRfGDvvOTeQJA/out-0.png" ], "started_at": "2024-03-19T19:02:06.859497Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/gbtx2rlbynvsbb6a4relxdluzy", "cancel": "https://api.replicate.com/v1/predictions/gbtx2rlbynvsbb6a4relxdluzy/cancel" }, "version": "914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b" }Generated inUsing seed: 12896 Ensuring enough disk space... Free disk space: 2469572575232 Downloading weights: https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar 2024-03-19T19:02:06Z | INFO | [ Initiating ] dest=/src/weights-cache/3708132d63d38faa minimum_chunk_size=150M url=https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar 2024-03-19T19:02:09Z | INFO | [ Complete ] dest=/src/weights-cache/3708132d63d38faa size="186 MB" total_elapsed=2.113s url=https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar b'' Downloaded weights in 2.2480790615081787 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: art deco <s0><s1> mandala design, big white patches, coloring pages for kids, illustration, white background, clean lines, line art txt2img mode 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:07, 3.66it/s] 7%|▋ | 2/30 [00:00<00:07, 3.66it/s] 10%|█ | 3/30 [00:00<00:07, 3.66it/s] 13%|█▎ | 4/30 [00:01<00:07, 3.65it/s] 17%|█▋ | 5/30 [00:01<00:06, 3.64it/s] 20%|██ | 6/30 [00:01<00:06, 3.64it/s] 23%|██▎ | 7/30 [00:01<00:06, 3.64it/s] 27%|██▋ | 8/30 [00:02<00:06, 3.63it/s] 30%|███ | 9/30 [00:02<00:05, 3.64it/s] 33%|███▎ | 10/30 [00:02<00:05, 3.63it/s] 37%|███▋ | 11/30 [00:03<00:05, 3.63it/s] 40%|████ | 12/30 [00:03<00:04, 3.63it/s] 43%|████▎ | 13/30 [00:03<00:04, 3.63it/s] 47%|████▋ | 14/30 [00:03<00:04, 3.63it/s] 50%|█████ | 15/30 [00:04<00:04, 3.63it/s] 53%|█████▎ | 16/30 [00:04<00:03, 3.63it/s] 57%|█████▋ | 17/30 [00:04<00:03, 3.63it/s] 60%|██████ | 18/30 [00:04<00:03, 3.63it/s] 63%|██████▎ | 19/30 [00:05<00:03, 3.63it/s] 67%|██████▋ | 20/30 [00:05<00:02, 3.63it/s] 70%|███████ | 21/30 [00:05<00:02, 3.63it/s] 73%|███████▎ | 22/30 [00:06<00:02, 3.63it/s] 77%|███████▋ | 23/30 [00:06<00:01, 3.63it/s] 80%|████████ | 24/30 [00:06<00:01, 3.63it/s] 83%|████████▎ | 25/30 [00:06<00:01, 3.62it/s] 87%|████████▋ | 26/30 [00:07<00:01, 3.63it/s] 90%|█████████ | 27/30 [00:07<00:00, 3.63it/s] 93%|█████████▎| 28/30 [00:07<00:00, 3.62it/s] 97%|█████████▋| 29/30 [00:07<00:00, 3.62it/s] 100%|██████████| 30/30 [00:08<00:00, 3.62it/s] 100%|██████████| 30/30 [00:08<00:00, 3.63it/s]Prediction
codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8bIDerarfgdbxbsjufsvtjjwh42m7yStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- a flower TOK mandal design, coloring pages for kids, illustration, white 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
- 30
{ "width": 1024, "height": 1024, "prompt": "a flower TOK mandal design, coloring pages for kids, illustration, white background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run codingdudecom/sdxl-mandala using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", { input: { width: 1024, height: 1024, prompt: "a flower TOK mandal design, coloring pages for kids, illustration, white background", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.8, negative_prompt: "", prompt_strength: 0.8, num_inference_steps: 30 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun codingdudecom/sdxl-mandala using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", input={ "width": 1024, "height": 1024, "prompt": "a flower TOK mandal design, coloring pages for kids, illustration, white background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run codingdudecom/sdxl-mandala 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": "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", "input": { "width": 1024, "height": 1024, "prompt": "a flower TOK mandal design, coloring pages for kids, illustration, white background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-03-19T15:08:38.876058Z", "created_at": "2024-03-19T15:08:24.066398Z", "data_removed": false, "error": null, "id": "erarfgdbxbsjufsvtjjwh42m7y", "input": { "width": 1024, "height": 1024, "prompt": "a flower TOK mandal design, coloring pages for kids, illustration, white background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 36811\nEnsuring enough disk space...\nFree disk space: 3363049660416\nDownloading weights: https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar\n2024-03-19T15:08:27Z | INFO | [ Initiating ] dest=/src/weights-cache/3708132d63d38faa minimum_chunk_size=150M url=https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar\n2024-03-19T15:08:28Z | INFO | [ Complete ] dest=/src/weights-cache/3708132d63d38faa size=\"186 MB\" total_elapsed=0.443s url=https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar\nb''\nDownloaded weights in 0.5244059562683105 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: a flower <s0><s1> mandal design, coloring pages for kids, illustration, white background\ntxt2img mode\n 0%| | 0/30 [00:00<?, ?it/s]/usr/local/lib/python3.9/site-packages/torch/nn/modules/conv.py:459: UserWarning: Applied workaround for CuDNN issue, install nvrtc.so (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:80.)\nreturn F.conv2d(input, weight, bias, self.stride,\n 3%|▎ | 1/30 [00:00<00:11, 2.48it/s]\n 7%|▋ | 2/30 [00:00<00:08, 3.14it/s]\n 10%|█ | 3/30 [00:00<00:07, 3.42it/s]\n 13%|█▎ | 4/30 [00:01<00:07, 3.57it/s]\n 17%|█▋ | 5/30 [00:01<00:06, 3.66it/s]\n 20%|██ | 6/30 [00:01<00:06, 3.71it/s]\n 23%|██▎ | 7/30 [00:01<00:06, 3.75it/s]\n 27%|██▋ | 8/30 [00:02<00:05, 3.78it/s]\n 30%|███ | 9/30 [00:02<00:05, 3.79it/s]\n 33%|███▎ | 10/30 [00:02<00:05, 3.80it/s]\n 37%|███▋ | 11/30 [00:03<00:04, 3.81it/s]\n 40%|████ | 12/30 [00:03<00:04, 3.81it/s]\n 43%|████▎ | 13/30 [00:03<00:04, 3.82it/s]\n 47%|████▋ | 14/30 [00:03<00:04, 3.82it/s]\n 50%|█████ | 15/30 [00:04<00:03, 3.82it/s]\n 53%|█████▎ | 16/30 [00:04<00:03, 3.82it/s]\n 57%|█████▋ | 17/30 [00:04<00:03, 3.81it/s]\n 60%|██████ | 18/30 [00:04<00:03, 3.82it/s]\n 63%|██████▎ | 19/30 [00:05<00:02, 3.81it/s]\n 67%|██████▋ | 20/30 [00:05<00:02, 3.81it/s]\n 70%|███████ | 21/30 [00:05<00:02, 3.81it/s]\n 73%|███████▎ | 22/30 [00:05<00:02, 3.81it/s]\n 77%|███████▋ | 23/30 [00:06<00:01, 3.81it/s]\n 80%|████████ | 24/30 [00:06<00:01, 3.81it/s]\n 83%|████████▎ | 25/30 [00:06<00:01, 3.81it/s]\n 87%|████████▋ | 26/30 [00:06<00:01, 3.80it/s]\n 90%|█████████ | 27/30 [00:07<00:00, 3.81it/s]\n 93%|█████████▎| 28/30 [00:07<00:00, 3.80it/s]\n 97%|█████████▋| 29/30 [00:07<00:00, 3.80it/s]\n100%|██████████| 30/30 [00:08<00:00, 3.80it/s]\n100%|██████████| 30/30 [00:08<00:00, 3.75it/s]", "metrics": { "predict_time": 10.959069, "total_time": 14.80966 }, "output": [ "https://replicate.delivery/pbxt/9Rl9laSO9LJEFRTd4fpvrCTCndUOhFOnPEv46FI9PgP746QJA/out-0.png" ], "started_at": "2024-03-19T15:08:27.916989Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/erarfgdbxbsjufsvtjjwh42m7y", "cancel": "https://api.replicate.com/v1/predictions/erarfgdbxbsjufsvtjjwh42m7y/cancel" }, "version": "914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b" }Generated inUsing seed: 36811 Ensuring enough disk space... Free disk space: 3363049660416 Downloading weights: https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar 2024-03-19T15:08:27Z | INFO | [ Initiating ] dest=/src/weights-cache/3708132d63d38faa minimum_chunk_size=150M url=https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar 2024-03-19T15:08:28Z | INFO | [ Complete ] dest=/src/weights-cache/3708132d63d38faa size="186 MB" total_elapsed=0.443s url=https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar b'' Downloaded weights in 0.5244059562683105 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: a flower <s0><s1> mandal design, coloring pages for kids, illustration, white background txt2img mode 0%| | 0/30 [00:00<?, ?it/s]/usr/local/lib/python3.9/site-packages/torch/nn/modules/conv.py:459: UserWarning: Applied workaround for CuDNN issue, install nvrtc.so (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:80.) return F.conv2d(input, weight, bias, self.stride, 3%|▎ | 1/30 [00:00<00:11, 2.48it/s] 7%|▋ | 2/30 [00:00<00:08, 3.14it/s] 10%|█ | 3/30 [00:00<00:07, 3.42it/s] 13%|█▎ | 4/30 [00:01<00:07, 3.57it/s] 17%|█▋ | 5/30 [00:01<00:06, 3.66it/s] 20%|██ | 6/30 [00:01<00:06, 3.71it/s] 23%|██▎ | 7/30 [00:01<00:06, 3.75it/s] 27%|██▋ | 8/30 [00:02<00:05, 3.78it/s] 30%|███ | 9/30 [00:02<00:05, 3.79it/s] 33%|███▎ | 10/30 [00:02<00:05, 3.80it/s] 37%|███▋ | 11/30 [00:03<00:04, 3.81it/s] 40%|████ | 12/30 [00:03<00:04, 3.81it/s] 43%|████▎ | 13/30 [00:03<00:04, 3.82it/s] 47%|████▋ | 14/30 [00:03<00:04, 3.82it/s] 50%|█████ | 15/30 [00:04<00:03, 3.82it/s] 53%|█████▎ | 16/30 [00:04<00:03, 3.82it/s] 57%|█████▋ | 17/30 [00:04<00:03, 3.81it/s] 60%|██████ | 18/30 [00:04<00:03, 3.82it/s] 63%|██████▎ | 19/30 [00:05<00:02, 3.81it/s] 67%|██████▋ | 20/30 [00:05<00:02, 3.81it/s] 70%|███████ | 21/30 [00:05<00:02, 3.81it/s] 73%|███████▎ | 22/30 [00:05<00:02, 3.81it/s] 77%|███████▋ | 23/30 [00:06<00:01, 3.81it/s] 80%|████████ | 24/30 [00:06<00:01, 3.81it/s] 83%|████████▎ | 25/30 [00:06<00:01, 3.81it/s] 87%|████████▋ | 26/30 [00:06<00:01, 3.80it/s] 90%|█████████ | 27/30 [00:07<00:00, 3.81it/s] 93%|█████████▎| 28/30 [00:07<00:00, 3.80it/s] 97%|█████████▋| 29/30 [00:07<00:00, 3.80it/s] 100%|██████████| 30/30 [00:08<00:00, 3.80it/s] 100%|██████████| 30/30 [00:08<00:00, 3.75it/s]Prediction
codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8bIDda3sudtbmwtad6eeo6654kh3oqStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- rose flower TOK mandal design, coloring pages for kids, illustration, white background, clean lines, line art
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 1
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- bad quality, ugly
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 1024, "height": 1024, "prompt": "rose flower TOK mandal design, coloring pages for kids, illustration, white background, clean lines, line art", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 1, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run codingdudecom/sdxl-mandala using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", { input: { width: 1024, height: 1024, prompt: "rose flower TOK mandal design, coloring pages for kids, illustration, white background, clean lines, line art", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 1, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.8, negative_prompt: "bad quality, ugly", prompt_strength: 0.8, num_inference_steps: 30 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun codingdudecom/sdxl-mandala using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", input={ "width": 1024, "height": 1024, "prompt": "rose flower TOK mandal design, coloring pages for kids, illustration, white background, clean lines, line art", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 1, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.8, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run codingdudecom/sdxl-mandala 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": "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", "input": { "width": 1024, "height": 1024, "prompt": "rose flower TOK mandal design, coloring pages for kids, illustration, white background, clean lines, line art", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 1, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-03-19T15:54:54.626188Z", "created_at": "2024-03-19T15:54:40.998027Z", "data_removed": false, "error": null, "id": "da3sudtbmwtad6eeo6654kh3oq", "input": { "width": 1024, "height": 1024, "prompt": "rose flower TOK mandal design, coloring pages for kids, illustration, white background, clean lines, line art", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 1, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 47595\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: rose flower <s0><s1> mandal design, coloring pages for kids, illustration, white background, clean lines, line art\ntxt2img mode\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:07, 3.68it/s]\n 7%|▋ | 2/30 [00:00<00:07, 3.68it/s]\n 10%|█ | 3/30 [00:00<00:07, 3.69it/s]\n 13%|█▎ | 4/30 [00:01<00:07, 3.68it/s]\n 17%|█▋ | 5/30 [00:01<00:06, 3.68it/s]\n 20%|██ | 6/30 [00:01<00:06, 3.68it/s]\n 23%|██▎ | 7/30 [00:01<00:06, 3.68it/s]\n 27%|██▋ | 8/30 [00:02<00:05, 3.67it/s]\n 30%|███ | 9/30 [00:02<00:05, 3.67it/s]\n 33%|███▎ | 10/30 [00:02<00:05, 3.68it/s]\n 37%|███▋ | 11/30 [00:02<00:05, 3.68it/s]\n 40%|████ | 12/30 [00:03<00:04, 3.67it/s]\n 43%|████▎ | 13/30 [00:03<00:04, 3.68it/s]\n 47%|████▋ | 14/30 [00:03<00:04, 3.67it/s]\n 50%|█████ | 15/30 [00:04<00:04, 3.67it/s]\n 53%|█████▎ | 16/30 [00:04<00:03, 3.67it/s]\n 57%|█████▋ | 17/30 [00:04<00:03, 3.68it/s]\n 60%|██████ | 18/30 [00:04<00:03, 3.67it/s]\n 63%|██████▎ | 19/30 [00:05<00:02, 3.67it/s]\n 67%|██████▋ | 20/30 [00:05<00:02, 3.67it/s]\n 70%|███████ | 21/30 [00:05<00:02, 3.67it/s]\n 73%|███████▎ | 22/30 [00:05<00:02, 3.67it/s]\n 77%|███████▋ | 23/30 [00:06<00:01, 3.66it/s]\n 80%|████████ | 24/30 [00:06<00:01, 3.66it/s]\n 83%|████████▎ | 25/30 [00:06<00:01, 3.66it/s]\n 87%|████████▋ | 26/30 [00:07<00:01, 3.66it/s]\n 90%|█████████ | 27/30 [00:07<00:00, 3.66it/s]\n 93%|█████████▎| 28/30 [00:07<00:00, 3.66it/s]\n 97%|█████████▋| 29/30 [00:07<00:00, 3.66it/s]\n100%|██████████| 30/30 [00:08<00:00, 3.66it/s]\n100%|██████████| 30/30 [00:08<00:00, 3.67it/s]", "metrics": { "predict_time": 10.089783, "total_time": 13.628161 }, "output": [ "https://replicate.delivery/pbxt/OF7SiZoLqJp8O5Pmsln1jDLTPM3cmpLNXZkqSnreI9cnO7QJA/out-0.png" ], "started_at": "2024-03-19T15:54:44.536405Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/da3sudtbmwtad6eeo6654kh3oq", "cancel": "https://api.replicate.com/v1/predictions/da3sudtbmwtad6eeo6654kh3oq/cancel" }, "version": "914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b" }Generated inUsing seed: 47595 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: rose flower <s0><s1> mandal design, coloring pages for kids, illustration, white background, clean lines, line art txt2img mode 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:07, 3.68it/s] 7%|▋ | 2/30 [00:00<00:07, 3.68it/s] 10%|█ | 3/30 [00:00<00:07, 3.69it/s] 13%|█▎ | 4/30 [00:01<00:07, 3.68it/s] 17%|█▋ | 5/30 [00:01<00:06, 3.68it/s] 20%|██ | 6/30 [00:01<00:06, 3.68it/s] 23%|██▎ | 7/30 [00:01<00:06, 3.68it/s] 27%|██▋ | 8/30 [00:02<00:05, 3.67it/s] 30%|███ | 9/30 [00:02<00:05, 3.67it/s] 33%|███▎ | 10/30 [00:02<00:05, 3.68it/s] 37%|███▋ | 11/30 [00:02<00:05, 3.68it/s] 40%|████ | 12/30 [00:03<00:04, 3.67it/s] 43%|████▎ | 13/30 [00:03<00:04, 3.68it/s] 47%|████▋ | 14/30 [00:03<00:04, 3.67it/s] 50%|█████ | 15/30 [00:04<00:04, 3.67it/s] 53%|█████▎ | 16/30 [00:04<00:03, 3.67it/s] 57%|█████▋ | 17/30 [00:04<00:03, 3.68it/s] 60%|██████ | 18/30 [00:04<00:03, 3.67it/s] 63%|██████▎ | 19/30 [00:05<00:02, 3.67it/s] 67%|██████▋ | 20/30 [00:05<00:02, 3.67it/s] 70%|███████ | 21/30 [00:05<00:02, 3.67it/s] 73%|███████▎ | 22/30 [00:05<00:02, 3.67it/s] 77%|███████▋ | 23/30 [00:06<00:01, 3.66it/s] 80%|████████ | 24/30 [00:06<00:01, 3.66it/s] 83%|████████▎ | 25/30 [00:06<00:01, 3.66it/s] 87%|████████▋ | 26/30 [00:07<00:01, 3.66it/s] 90%|█████████ | 27/30 [00:07<00:00, 3.66it/s] 93%|█████████▎| 28/30 [00:07<00:00, 3.66it/s] 97%|█████████▋| 29/30 [00:07<00:00, 3.66it/s] 100%|██████████| 30/30 [00:08<00:00, 3.66it/s] 100%|██████████| 30/30 [00:08<00:00, 3.67it/s]Prediction
codingdudecom/sdxl-mandala:a93e82a77fce729a086caf532323ee798f89c433871ad2921e6fa0c3978e9bdaIDiy3wad3bofabql36672qht7hgyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- a minimalist bird design in the style TOK, coloring pages for kids, illustration, round circle, white background
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.8
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.6
- negative_prompt
- bad quality, ugly
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 1024, "height": 1024, "prompt": "a minimalist bird design in the style TOK, coloring pages for kids, illustration, round circle, white background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.6, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run codingdudecom/sdxl-mandala using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "codingdudecom/sdxl-mandala:a93e82a77fce729a086caf532323ee798f89c433871ad2921e6fa0c3978e9bda", { input: { width: 1024, height: 1024, prompt: "a minimalist bird design in the style TOK, coloring pages for kids, illustration, round circle, white background", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.8, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.6, negative_prompt: "bad quality, ugly", prompt_strength: 0.8, num_inference_steps: 30 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun codingdudecom/sdxl-mandala using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "codingdudecom/sdxl-mandala:a93e82a77fce729a086caf532323ee798f89c433871ad2921e6fa0c3978e9bda", input={ "width": 1024, "height": 1024, "prompt": "a minimalist bird design in the style TOK, coloring pages for kids, illustration, round circle, white background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.6, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run codingdudecom/sdxl-mandala 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": "codingdudecom/sdxl-mandala:a93e82a77fce729a086caf532323ee798f89c433871ad2921e6fa0c3978e9bda", "input": { "width": 1024, "height": 1024, "prompt": "a minimalist bird design in the style TOK, coloring pages for kids, illustration, round circle, white background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.6, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-03-19T19:47:00.847737Z", "created_at": "2024-03-19T19:46:46.587564Z", "data_removed": false, "error": null, "id": "iy3wad3bofabql36672qht7hgy", "input": { "width": 1024, "height": 1024, "prompt": "a minimalist bird design in the style TOK, coloring pages for kids, illustration, round circle, white background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.6, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 32518\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: a minimalist bird design in the style <s0><s1>, coloring pages for kids, illustration, round circle, white background\ntxt2img mode\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:07, 3.83it/s]\n 7%|▋ | 2/30 [00:00<00:07, 3.82it/s]\n 10%|█ | 3/30 [00:00<00:07, 3.81it/s]\n 13%|█▎ | 4/30 [00:01<00:06, 3.79it/s]\n 17%|█▋ | 5/30 [00:01<00:06, 3.80it/s]\n 20%|██ | 6/30 [00:01<00:06, 3.80it/s]\n 23%|██▎ | 7/30 [00:01<00:06, 3.79it/s]\n 27%|██▋ | 8/30 [00:02<00:05, 3.79it/s]\n 30%|███ | 9/30 [00:02<00:05, 3.79it/s]\n 33%|███▎ | 10/30 [00:02<00:05, 3.79it/s]\n 37%|███▋ | 11/30 [00:02<00:05, 3.78it/s]\n 40%|████ | 12/30 [00:03<00:04, 3.78it/s]\n 43%|████▎ | 13/30 [00:03<00:04, 3.79it/s]\n 47%|████▋ | 14/30 [00:03<00:04, 3.79it/s]\n 50%|█████ | 15/30 [00:03<00:03, 3.79it/s]\n 53%|█████▎ | 16/30 [00:04<00:03, 3.78it/s]\n 57%|█████▋ | 17/30 [00:04<00:03, 3.78it/s]\n 60%|██████ | 18/30 [00:04<00:03, 3.78it/s]\n 63%|██████▎ | 19/30 [00:05<00:02, 3.78it/s]\n 67%|██████▋ | 20/30 [00:05<00:02, 3.78it/s]\n 70%|███████ | 21/30 [00:05<00:02, 3.78it/s]\n 73%|███████▎ | 22/30 [00:05<00:02, 3.78it/s]\n 77%|███████▋ | 23/30 [00:06<00:01, 3.77it/s]\n 80%|████████ | 24/30 [00:06<00:01, 3.77it/s]\n 83%|████████▎ | 25/30 [00:06<00:01, 3.78it/s]\n 87%|████████▋ | 26/30 [00:06<00:01, 3.77it/s]\n 90%|█████████ | 27/30 [00:07<00:00, 3.77it/s]\n 93%|█████████▎| 28/30 [00:07<00:00, 3.77it/s]\n 97%|█████████▋| 29/30 [00:07<00:00, 3.77it/s]\n100%|██████████| 30/30 [00:07<00:00, 3.77it/s]\n100%|██████████| 30/30 [00:07<00:00, 3.78it/s]", "metrics": { "predict_time": 10.887572, "total_time": 14.260173 }, "output": [ "https://replicate.delivery/pbxt/6r4OeoPVdhxCfEsXKEyZHVTGygkQmWYoYESDvOEKncyz25hSA/out-0.png" ], "started_at": "2024-03-19T19:46:49.960165Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/iy3wad3bofabql36672qht7hgy", "cancel": "https://api.replicate.com/v1/predictions/iy3wad3bofabql36672qht7hgy/cancel" }, "version": "a93e82a77fce729a086caf532323ee798f89c433871ad2921e6fa0c3978e9bda" }Generated inUsing seed: 32518 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: a minimalist bird design in the style <s0><s1>, coloring pages for kids, illustration, round circle, white background txt2img mode 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:07, 3.83it/s] 7%|▋ | 2/30 [00:00<00:07, 3.82it/s] 10%|█ | 3/30 [00:00<00:07, 3.81it/s] 13%|█▎ | 4/30 [00:01<00:06, 3.79it/s] 17%|█▋ | 5/30 [00:01<00:06, 3.80it/s] 20%|██ | 6/30 [00:01<00:06, 3.80it/s] 23%|██▎ | 7/30 [00:01<00:06, 3.79it/s] 27%|██▋ | 8/30 [00:02<00:05, 3.79it/s] 30%|███ | 9/30 [00:02<00:05, 3.79it/s] 33%|███▎ | 10/30 [00:02<00:05, 3.79it/s] 37%|███▋ | 11/30 [00:02<00:05, 3.78it/s] 40%|████ | 12/30 [00:03<00:04, 3.78it/s] 43%|████▎ | 13/30 [00:03<00:04, 3.79it/s] 47%|████▋ | 14/30 [00:03<00:04, 3.79it/s] 50%|█████ | 15/30 [00:03<00:03, 3.79it/s] 53%|█████▎ | 16/30 [00:04<00:03, 3.78it/s] 57%|█████▋ | 17/30 [00:04<00:03, 3.78it/s] 60%|██████ | 18/30 [00:04<00:03, 3.78it/s] 63%|██████▎ | 19/30 [00:05<00:02, 3.78it/s] 67%|██████▋ | 20/30 [00:05<00:02, 3.78it/s] 70%|███████ | 21/30 [00:05<00:02, 3.78it/s] 73%|███████▎ | 22/30 [00:05<00:02, 3.78it/s] 77%|███████▋ | 23/30 [00:06<00:01, 3.77it/s] 80%|████████ | 24/30 [00:06<00:01, 3.77it/s] 83%|████████▎ | 25/30 [00:06<00:01, 3.78it/s] 87%|████████▋ | 26/30 [00:06<00:01, 3.77it/s] 90%|█████████ | 27/30 [00:07<00:00, 3.77it/s] 93%|█████████▎| 28/30 [00:07<00:00, 3.77it/s] 97%|█████████▋| 29/30 [00:07<00:00, 3.77it/s] 100%|██████████| 30/30 [00:07<00:00, 3.77it/s] 100%|██████████| 30/30 [00:07<00:00, 3.78it/s]Prediction
codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8bIDtvxmnctbav4fghfafwm36ecc7qStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- a round TOK mandal design with triangles, coloring pages for kids, illustration, white background
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.8
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 1024, "height": 1024, "prompt": "a round TOK mandal design with triangles, coloring pages for kids, illustration, white background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run codingdudecom/sdxl-mandala using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", { input: { width: 1024, height: 1024, prompt: "a round TOK mandal design with triangles, coloring pages for kids, illustration, white background", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.8, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.8, negative_prompt: "", prompt_strength: 0.8, num_inference_steps: 30 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun codingdudecom/sdxl-mandala using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", input={ "width": 1024, "height": 1024, "prompt": "a round TOK mandal design with triangles, coloring pages for kids, illustration, white background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run codingdudecom/sdxl-mandala 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": "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", "input": { "width": 1024, "height": 1024, "prompt": "a round TOK mandal design with triangles, coloring pages for kids, illustration, white background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-03-19T15:11:27.113465Z", "created_at": "2024-03-19T15:11:07.071096Z", "data_removed": false, "error": null, "id": "tvxmnctbav4fghfafwm36ecc7q", "input": { "width": 1024, "height": 1024, "prompt": "a round TOK mandal design with triangles, coloring pages for kids, illustration, white background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 21018\nEnsuring enough disk space...\nFree disk space: 2023003336704\nDownloading weights: https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar\n2024-03-19T15:11:09Z | INFO | [ Initiating ] dest=/src/weights-cache/3708132d63d38faa minimum_chunk_size=150M url=https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar\n2024-03-19T15:11:15Z | INFO | [ Complete ] dest=/src/weights-cache/3708132d63d38faa size=\"186 MB\" total_elapsed=5.877s url=https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar\nb''\nDownloaded weights in 6.066521167755127 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: a round <s0><s1> mandal design with triangles, coloring pages for kids, illustration, white background\ntxt2img mode\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:07, 3.66it/s]\n 7%|▋ | 2/30 [00:00<00:07, 3.65it/s]\n 10%|█ | 3/30 [00:00<00:07, 3.65it/s]\n 13%|█▎ | 4/30 [00:01<00:07, 3.64it/s]\n 17%|█▋ | 5/30 [00:01<00:06, 3.64it/s]\n 20%|██ | 6/30 [00:01<00:06, 3.64it/s]\n 23%|██▎ | 7/30 [00:01<00:06, 3.64it/s]\n 27%|██▋ | 8/30 [00:02<00:06, 3.63it/s]\n 30%|███ | 9/30 [00:02<00:05, 3.64it/s]\n 33%|███▎ | 10/30 [00:02<00:05, 3.64it/s]\n 37%|███▋ | 11/30 [00:03<00:05, 3.63it/s]\n 40%|████ | 12/30 [00:03<00:04, 3.64it/s]\n 43%|████▎ | 13/30 [00:03<00:04, 3.63it/s]\n 47%|████▋ | 14/30 [00:03<00:04, 3.63it/s]\n 50%|█████ | 15/30 [00:04<00:04, 3.63it/s]\n 53%|█████▎ | 16/30 [00:04<00:03, 3.63it/s]\n 57%|█████▋ | 17/30 [00:04<00:03, 3.64it/s]\n 60%|██████ | 18/30 [00:04<00:03, 3.65it/s]\n 63%|██████▎ | 19/30 [00:05<00:03, 3.65it/s]\n 67%|██████▋ | 20/30 [00:05<00:02, 3.65it/s]\n 70%|███████ | 21/30 [00:05<00:02, 3.65it/s]\n 73%|███████▎ | 22/30 [00:06<00:02, 3.66it/s]\n 77%|███████▋ | 23/30 [00:06<00:01, 3.65it/s]\n 80%|████████ | 24/30 [00:06<00:01, 3.65it/s]\n 83%|████████▎ | 25/30 [00:06<00:01, 3.65it/s]\n 87%|████████▋ | 26/30 [00:07<00:01, 3.65it/s]\n 90%|█████████ | 27/30 [00:07<00:00, 3.65it/s]\n 93%|█████████▎| 28/30 [00:07<00:00, 3.65it/s]\n 97%|█████████▋| 29/30 [00:07<00:00, 3.65it/s]\n100%|██████████| 30/30 [00:08<00:00, 3.65it/s]\n100%|██████████| 30/30 [00:08<00:00, 3.64it/s]", "metrics": { "predict_time": 17.264503, "total_time": 20.042369 }, "output": [ "https://replicate.delivery/pbxt/ubYGbYhQ5VLGHdieYOAb2Uob1FXaAblzb2AM9ERsGJ7O66QJA/out-0.png" ], "started_at": "2024-03-19T15:11:09.848962Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/tvxmnctbav4fghfafwm36ecc7q", "cancel": "https://api.replicate.com/v1/predictions/tvxmnctbav4fghfafwm36ecc7q/cancel" }, "version": "914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b" }Generated inUsing seed: 21018 Ensuring enough disk space... Free disk space: 2023003336704 Downloading weights: https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar 2024-03-19T15:11:09Z | INFO | [ Initiating ] dest=/src/weights-cache/3708132d63d38faa minimum_chunk_size=150M url=https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar 2024-03-19T15:11:15Z | INFO | [ Complete ] dest=/src/weights-cache/3708132d63d38faa size="186 MB" total_elapsed=5.877s url=https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar b'' Downloaded weights in 6.066521167755127 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: a round <s0><s1> mandal design with triangles, coloring pages for kids, illustration, white background txt2img mode 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:07, 3.66it/s] 7%|▋ | 2/30 [00:00<00:07, 3.65it/s] 10%|█ | 3/30 [00:00<00:07, 3.65it/s] 13%|█▎ | 4/30 [00:01<00:07, 3.64it/s] 17%|█▋ | 5/30 [00:01<00:06, 3.64it/s] 20%|██ | 6/30 [00:01<00:06, 3.64it/s] 23%|██▎ | 7/30 [00:01<00:06, 3.64it/s] 27%|██▋ | 8/30 [00:02<00:06, 3.63it/s] 30%|███ | 9/30 [00:02<00:05, 3.64it/s] 33%|███▎ | 10/30 [00:02<00:05, 3.64it/s] 37%|███▋ | 11/30 [00:03<00:05, 3.63it/s] 40%|████ | 12/30 [00:03<00:04, 3.64it/s] 43%|████▎ | 13/30 [00:03<00:04, 3.63it/s] 47%|████▋ | 14/30 [00:03<00:04, 3.63it/s] 50%|█████ | 15/30 [00:04<00:04, 3.63it/s] 53%|█████▎ | 16/30 [00:04<00:03, 3.63it/s] 57%|█████▋ | 17/30 [00:04<00:03, 3.64it/s] 60%|██████ | 18/30 [00:04<00:03, 3.65it/s] 63%|██████▎ | 19/30 [00:05<00:03, 3.65it/s] 67%|██████▋ | 20/30 [00:05<00:02, 3.65it/s] 70%|███████ | 21/30 [00:05<00:02, 3.65it/s] 73%|███████▎ | 22/30 [00:06<00:02, 3.66it/s] 77%|███████▋ | 23/30 [00:06<00:01, 3.65it/s] 80%|████████ | 24/30 [00:06<00:01, 3.65it/s] 83%|████████▎ | 25/30 [00:06<00:01, 3.65it/s] 87%|████████▋ | 26/30 [00:07<00:01, 3.65it/s] 90%|█████████ | 27/30 [00:07<00:00, 3.65it/s] 93%|█████████▎| 28/30 [00:07<00:00, 3.65it/s] 97%|█████████▋| 29/30 [00:07<00:00, 3.65it/s] 100%|██████████| 30/30 [00:08<00:00, 3.65it/s] 100%|██████████| 30/30 [00:08<00:00, 3.64it/s]Prediction
codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8bIDp6qggxdbyghyhfs4ivl2vz4duyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- lotus flower TOK mandal design, coloring pages for kids, illustration, white background, clean lines, line art
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.9
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- bad quality, ugly
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 1024, "height": 1024, "prompt": "lotus flower TOK mandal design, coloring pages for kids, illustration, white background, clean lines, line art", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run codingdudecom/sdxl-mandala using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", { input: { width: 1024, height: 1024, prompt: "lotus flower TOK mandal design, coloring pages for kids, illustration, white background, clean lines, line art", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.9, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.8, negative_prompt: "bad quality, ugly", prompt_strength: 0.8, num_inference_steps: 30 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun codingdudecom/sdxl-mandala using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", input={ "width": 1024, "height": 1024, "prompt": "lotus flower TOK mandal design, coloring pages for kids, illustration, white background, clean lines, line art", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.8, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run codingdudecom/sdxl-mandala 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": "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", "input": { "width": 1024, "height": 1024, "prompt": "lotus flower TOK mandal design, coloring pages for kids, illustration, white background, clean lines, line art", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-03-19T15:57:20.357305Z", "created_at": "2024-03-19T15:57:09.286153Z", "data_removed": false, "error": null, "id": "p6qggxdbyghyhfs4ivl2vz4duy", "input": { "width": 1024, "height": 1024, "prompt": "lotus flower TOK mandal design, coloring pages for kids, illustration, white background, clean lines, line art", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 10904\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: lotus flower <s0><s1> mandal design, coloring pages for kids, illustration, white background, clean lines, line art\ntxt2img mode\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:07, 3.67it/s]\n 7%|▋ | 2/30 [00:00<00:07, 3.65it/s]\n 10%|█ | 3/30 [00:00<00:07, 3.65it/s]\n 13%|█▎ | 4/30 [00:01<00:07, 3.65it/s]\n 17%|█▋ | 5/30 [00:01<00:06, 3.64it/s]\n 20%|██ | 6/30 [00:01<00:06, 3.64it/s]\n 23%|██▎ | 7/30 [00:01<00:06, 3.64it/s]\n 27%|██▋ | 8/30 [00:02<00:06, 3.64it/s]\n 30%|███ | 9/30 [00:02<00:05, 3.64it/s]\n 33%|███▎ | 10/30 [00:02<00:05, 3.64it/s]\n 37%|███▋ | 11/30 [00:03<00:05, 3.64it/s]\n 40%|████ | 12/30 [00:03<00:04, 3.64it/s]\n 43%|████▎ | 13/30 [00:03<00:04, 3.64it/s]\n 47%|████▋ | 14/30 [00:03<00:04, 3.64it/s]\n 50%|█████ | 15/30 [00:04<00:04, 3.63it/s]\n 53%|█████▎ | 16/30 [00:04<00:03, 3.63it/s]\n 57%|█████▋ | 17/30 [00:04<00:03, 3.63it/s]\n 60%|██████ | 18/30 [00:04<00:03, 3.63it/s]\n 63%|██████▎ | 19/30 [00:05<00:03, 3.63it/s]\n 67%|██████▋ | 20/30 [00:05<00:02, 3.63it/s]\n 70%|███████ | 21/30 [00:05<00:02, 3.63it/s]\n 73%|███████▎ | 22/30 [00:06<00:02, 3.63it/s]\n 77%|███████▋ | 23/30 [00:06<00:01, 3.63it/s]\n 80%|████████ | 24/30 [00:06<00:01, 3.63it/s]\n 83%|████████▎ | 25/30 [00:06<00:01, 3.63it/s]\n 87%|████████▋ | 26/30 [00:07<00:01, 3.63it/s]\n 90%|█████████ | 27/30 [00:07<00:00, 3.63it/s]\n 93%|█████████▎| 28/30 [00:07<00:00, 3.63it/s]\n 97%|█████████▋| 29/30 [00:07<00:00, 3.63it/s]\n100%|██████████| 30/30 [00:08<00:00, 3.63it/s]\n100%|██████████| 30/30 [00:08<00:00, 3.63it/s]", "metrics": { "predict_time": 10.121237, "total_time": 11.071152 }, "output": [ "https://replicate.delivery/pbxt/90f7ji7PyVQ4US8tMUFfBhBZHcoYUpUFJ4qLfCZ1ni7f9ZHKB/out-0.png" ], "started_at": "2024-03-19T15:57:10.236068Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/p6qggxdbyghyhfs4ivl2vz4duy", "cancel": "https://api.replicate.com/v1/predictions/p6qggxdbyghyhfs4ivl2vz4duy/cancel" }, "version": "914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b" }Generated inUsing seed: 10904 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: lotus flower <s0><s1> mandal design, coloring pages for kids, illustration, white background, clean lines, line art txt2img mode 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:07, 3.67it/s] 7%|▋ | 2/30 [00:00<00:07, 3.65it/s] 10%|█ | 3/30 [00:00<00:07, 3.65it/s] 13%|█▎ | 4/30 [00:01<00:07, 3.65it/s] 17%|█▋ | 5/30 [00:01<00:06, 3.64it/s] 20%|██ | 6/30 [00:01<00:06, 3.64it/s] 23%|██▎ | 7/30 [00:01<00:06, 3.64it/s] 27%|██▋ | 8/30 [00:02<00:06, 3.64it/s] 30%|███ | 9/30 [00:02<00:05, 3.64it/s] 33%|███▎ | 10/30 [00:02<00:05, 3.64it/s] 37%|███▋ | 11/30 [00:03<00:05, 3.64it/s] 40%|████ | 12/30 [00:03<00:04, 3.64it/s] 43%|████▎ | 13/30 [00:03<00:04, 3.64it/s] 47%|████▋ | 14/30 [00:03<00:04, 3.64it/s] 50%|█████ | 15/30 [00:04<00:04, 3.63it/s] 53%|█████▎ | 16/30 [00:04<00:03, 3.63it/s] 57%|█████▋ | 17/30 [00:04<00:03, 3.63it/s] 60%|██████ | 18/30 [00:04<00:03, 3.63it/s] 63%|██████▎ | 19/30 [00:05<00:03, 3.63it/s] 67%|██████▋ | 20/30 [00:05<00:02, 3.63it/s] 70%|███████ | 21/30 [00:05<00:02, 3.63it/s] 73%|███████▎ | 22/30 [00:06<00:02, 3.63it/s] 77%|███████▋ | 23/30 [00:06<00:01, 3.63it/s] 80%|████████ | 24/30 [00:06<00:01, 3.63it/s] 83%|████████▎ | 25/30 [00:06<00:01, 3.63it/s] 87%|████████▋ | 26/30 [00:07<00:01, 3.63it/s] 90%|█████████ | 27/30 [00:07<00:00, 3.63it/s] 93%|█████████▎| 28/30 [00:07<00:00, 3.63it/s] 97%|█████████▋| 29/30 [00:07<00:00, 3.63it/s] 100%|██████████| 30/30 [00:08<00:00, 3.63it/s] 100%|██████████| 30/30 [00:08<00:00, 3.63it/s]Prediction
codingdudecom/sdxl-mandala:a93e82a77fce729a086caf532323ee798f89c433871ad2921e6fa0c3978e9bdaIDfrgvk43bxjlhq47exbd2rtfkkyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- a minimalist rose flower in the style TOK, coloring pages for kids, illustration, line art, round circle, white background
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.8
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.6
- negative_prompt
- bad quality, ugly
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 1024, "height": 1024, "prompt": "a minimalist rose flower in the style TOK, coloring pages for kids, illustration, line art, round circle, white background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.6, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run codingdudecom/sdxl-mandala using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "codingdudecom/sdxl-mandala:a93e82a77fce729a086caf532323ee798f89c433871ad2921e6fa0c3978e9bda", { input: { width: 1024, height: 1024, prompt: "a minimalist rose flower in the style TOK, coloring pages for kids, illustration, line art, round circle, white background", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.8, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.6, negative_prompt: "bad quality, ugly", prompt_strength: 0.8, num_inference_steps: 30 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun codingdudecom/sdxl-mandala using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "codingdudecom/sdxl-mandala:a93e82a77fce729a086caf532323ee798f89c433871ad2921e6fa0c3978e9bda", input={ "width": 1024, "height": 1024, "prompt": "a minimalist rose flower in the style TOK, coloring pages for kids, illustration, line art, round circle, white background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.6, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run codingdudecom/sdxl-mandala 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": "codingdudecom/sdxl-mandala:a93e82a77fce729a086caf532323ee798f89c433871ad2921e6fa0c3978e9bda", "input": { "width": 1024, "height": 1024, "prompt": "a minimalist rose flower in the style TOK, coloring pages for kids, illustration, line art, round circle, white background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.6, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-03-19T19:47:52.258840Z", "created_at": "2024-03-19T19:47:40.465486Z", "data_removed": false, "error": null, "id": "frgvk43bxjlhq47exbd2rtfkky", "input": { "width": 1024, "height": 1024, "prompt": "a minimalist rose flower in the style TOK, coloring pages for kids, illustration, line art, round circle, white background", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.6, "negative_prompt": "bad quality, ugly", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 59116\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: a minimalist rose flower in the style <s0><s1>, coloring pages for kids, illustration, line art, round circle, white background\ntxt2img mode\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:07, 3.82it/s]\n 7%|▋ | 2/30 [00:00<00:07, 3.82it/s]\n 10%|█ | 3/30 [00:00<00:07, 3.82it/s]\n 13%|█▎ | 4/30 [00:01<00:06, 3.81it/s]\n 17%|█▋ | 5/30 [00:01<00:06, 3.80it/s]\n 20%|██ | 6/30 [00:01<00:06, 3.81it/s]\n 23%|██▎ | 7/30 [00:01<00:06, 3.81it/s]\n 27%|██▋ | 8/30 [00:02<00:05, 3.80it/s]\n 30%|███ | 9/30 [00:02<00:05, 3.80it/s]\n 33%|███▎ | 10/30 [00:02<00:05, 3.80it/s]\n 37%|███▋ | 11/30 [00:02<00:04, 3.80it/s]\n 40%|████ | 12/30 [00:03<00:04, 3.80it/s]\n 43%|████▎ | 13/30 [00:03<00:04, 3.79it/s]\n 47%|████▋ | 14/30 [00:03<00:04, 3.80it/s]\n 50%|█████ | 15/30 [00:03<00:03, 3.80it/s]\n 53%|█████▎ | 16/30 [00:04<00:03, 3.79it/s]\n 57%|█████▋ | 17/30 [00:04<00:03, 3.79it/s]\n 60%|██████ | 18/30 [00:04<00:03, 3.79it/s]\n 63%|██████▎ | 19/30 [00:05<00:02, 3.79it/s]\n 67%|██████▋ | 20/30 [00:05<00:02, 3.79it/s]\n 70%|███████ | 21/30 [00:05<00:02, 3.79it/s]\n 73%|███████▎ | 22/30 [00:05<00:02, 3.79it/s]\n 77%|███████▋ | 23/30 [00:06<00:01, 3.79it/s]\n 80%|████████ | 24/30 [00:06<00:01, 3.79it/s]\n 83%|████████▎ | 25/30 [00:06<00:01, 3.79it/s]\n 87%|████████▋ | 26/30 [00:06<00:01, 3.79it/s]\n 90%|█████████ | 27/30 [00:07<00:00, 3.79it/s]\n 93%|█████████▎| 28/30 [00:07<00:00, 3.79it/s]\n 97%|█████████▋| 29/30 [00:07<00:00, 3.79it/s]\n100%|██████████| 30/30 [00:07<00:00, 3.79it/s]\n100%|██████████| 30/30 [00:07<00:00, 3.80it/s]", "metrics": { "predict_time": 10.70703, "total_time": 11.793354 }, "output": [ "https://replicate.delivery/pbxt/sbpjwEdRtRbYBhuZCPaIn89ZXfnzBeTP3AzoXigTffEbeOPUC/out-0.png" ], "started_at": "2024-03-19T19:47:41.551810Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/frgvk43bxjlhq47exbd2rtfkky", "cancel": "https://api.replicate.com/v1/predictions/frgvk43bxjlhq47exbd2rtfkky/cancel" }, "version": "a93e82a77fce729a086caf532323ee798f89c433871ad2921e6fa0c3978e9bda" }Generated inUsing seed: 59116 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: a minimalist rose flower in the style <s0><s1>, coloring pages for kids, illustration, line art, round circle, white background txt2img mode 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:07, 3.82it/s] 7%|▋ | 2/30 [00:00<00:07, 3.82it/s] 10%|█ | 3/30 [00:00<00:07, 3.82it/s] 13%|█▎ | 4/30 [00:01<00:06, 3.81it/s] 17%|█▋ | 5/30 [00:01<00:06, 3.80it/s] 20%|██ | 6/30 [00:01<00:06, 3.81it/s] 23%|██▎ | 7/30 [00:01<00:06, 3.81it/s] 27%|██▋ | 8/30 [00:02<00:05, 3.80it/s] 30%|███ | 9/30 [00:02<00:05, 3.80it/s] 33%|███▎ | 10/30 [00:02<00:05, 3.80it/s] 37%|███▋ | 11/30 [00:02<00:04, 3.80it/s] 40%|████ | 12/30 [00:03<00:04, 3.80it/s] 43%|████▎ | 13/30 [00:03<00:04, 3.79it/s] 47%|████▋ | 14/30 [00:03<00:04, 3.80it/s] 50%|█████ | 15/30 [00:03<00:03, 3.80it/s] 53%|█████▎ | 16/30 [00:04<00:03, 3.79it/s] 57%|█████▋ | 17/30 [00:04<00:03, 3.79it/s] 60%|██████ | 18/30 [00:04<00:03, 3.79it/s] 63%|██████▎ | 19/30 [00:05<00:02, 3.79it/s] 67%|██████▋ | 20/30 [00:05<00:02, 3.79it/s] 70%|███████ | 21/30 [00:05<00:02, 3.79it/s] 73%|███████▎ | 22/30 [00:05<00:02, 3.79it/s] 77%|███████▋ | 23/30 [00:06<00:01, 3.79it/s] 80%|████████ | 24/30 [00:06<00:01, 3.79it/s] 83%|████████▎ | 25/30 [00:06<00:01, 3.79it/s] 87%|████████▋ | 26/30 [00:06<00:01, 3.79it/s] 90%|█████████ | 27/30 [00:07<00:00, 3.79it/s] 93%|█████████▎| 28/30 [00:07<00:00, 3.79it/s] 97%|█████████▋| 29/30 [00:07<00:00, 3.79it/s] 100%|██████████| 30/30 [00:07<00:00, 3.79it/s] 100%|██████████| 30/30 [00:07<00:00, 3.80it/s]Prediction
codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8bIDmu467o3blfqzqt7gylybrafspqStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- a round TOK with swirls within swirls, coloring pages for kids, illustration, white background
- refine
- no_refiner
- scheduler
- KarrasDPM
- lora_scale
- 0.8
- 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": "a round TOK with swirls within swirls, coloring pages for kids, illustration, white background", "refine": "no_refiner", "scheduler": "KarrasDPM", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 }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 codingdudecom/sdxl-mandala using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", { input: { width: 1024, height: 1024, prompt: "a round TOK with swirls within swirls, coloring pages for kids, illustration, white background", refine: "no_refiner", scheduler: "KarrasDPM", lora_scale: 0.8, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.8, negative_prompt: "", prompt_strength: 0.8, num_inference_steps: 50 } } ); // 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 codingdudecom/sdxl-mandala using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", input={ "width": 1024, "height": 1024, "prompt": "a round TOK with swirls within swirls, coloring pages for kids, illustration, white background", "refine": "no_refiner", "scheduler": "KarrasDPM", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "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.
Run codingdudecom/sdxl-mandala 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": "codingdudecom/sdxl-mandala:914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b", "input": { "width": 1024, "height": 1024, "prompt": "a round TOK with swirls within swirls, coloring pages for kids, illustration, white background", "refine": "no_refiner", "scheduler": "KarrasDPM", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-03-19T15:13:37.269596Z", "created_at": "2024-03-19T15:13:14.583449Z", "data_removed": false, "error": null, "id": "mu467o3blfqzqt7gylybrafspq", "input": { "width": 1024, "height": 1024, "prompt": "a round TOK with swirls within swirls, coloring pages for kids, illustration, white background", "refine": "no_refiner", "scheduler": "KarrasDPM", "lora_scale": 0.8, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 13645\nEnsuring enough disk space...\nFree disk space: 1892361175040\nDownloading weights: https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar\n2024-03-19T15:13:21Z | INFO | [ Initiating ] dest=/src/weights-cache/3708132d63d38faa minimum_chunk_size=150M url=https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar\n2024-03-19T15:13:21Z | INFO | [ Complete ] dest=/src/weights-cache/3708132d63d38faa size=\"186 MB\" total_elapsed=0.555s url=https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar\nb''\nDownloaded weights in 0.6408822536468506 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: a round <s0><s1> with swirls within swirls, coloring pages for kids, illustration, white background\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.66it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.65it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.65it/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, 3.65it/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, 3.65it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.65it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.65it/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, 3.64it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.64it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.64it/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, 3.64it/s]\n 56%|█████▌ | 28/50 [00:07<00:06, 3.63it/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]\n98%|█████████▊| 49/50 [00:13<00:00, 3.63it/s]\n98%|█████████▊| 49/50 [00:13<00:00, 3.64it/s]", "metrics": { "predict_time": 15.904344, "total_time": 22.686147 }, "output": [ "https://replicate.delivery/pbxt/s3WSGcKIz34gA1yPW5FSPA0Y9eeoimPrW7tCKuYK3mtg21hSA/out-0.png" ], "started_at": "2024-03-19T15:13:21.365252Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/mu467o3blfqzqt7gylybrafspq", "cancel": "https://api.replicate.com/v1/predictions/mu467o3blfqzqt7gylybrafspq/cancel" }, "version": "914b95a0a2b4ba91dcbff37d28d2c12081bd183c37c50bff865eff96b9252e8b" }Generated inUsing seed: 13645 Ensuring enough disk space... Free disk space: 1892361175040 Downloading weights: https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar 2024-03-19T15:13:21Z | INFO | [ Initiating ] dest=/src/weights-cache/3708132d63d38faa minimum_chunk_size=150M url=https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar 2024-03-19T15:13:21Z | INFO | [ Complete ] dest=/src/weights-cache/3708132d63d38faa size="186 MB" total_elapsed=0.555s url=https://replicate.delivery/pbxt/hRVGxmMRULIfCaVfeyCOaIy3zDcK0iyiW8uN0k06gafukWHKB/trained_model.tar b'' Downloaded weights in 0.6408822536468506 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: a round <s0><s1> with swirls within swirls, coloring pages for kids, illustration, white background txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.66it/s] 4%|▍ | 2/50 [00:00<00:13, 3.65it/s] 6%|▌ | 3/50 [00:00<00:12, 3.65it/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, 3.65it/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, 3.65it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.65it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.65it/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, 3.64it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.64it/s] 40%|████ | 20/50 [00:05<00:08, 3.64it/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, 3.64it/s] 56%|█████▌ | 28/50 [00:07<00:06, 3.63it/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] 98%|█████████▊| 49/50 [00:13<00:00, 3.64it/s]
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