nandycc
/
sdxl-mascot-avatars
Fine tuned to generate cute mascot avatars, by aistartupkit.com
- Public
- 12.9K runs
-
L40S
- SDXL fine-tune
Prediction
nandycc/sdxl-mascot-avatars:f0f8a157ID6cj36ytbc2b3jbghudm23vfsziStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of TOK, Cute police dog
- 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
- 26
{ "width": 1024, "height": 1024, "prompt": "In the style of TOK, Cute police dog", "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": 26 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run nandycc/sdxl-mascot-avatars using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nandycc/sdxl-mascot-avatars:f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", { input: { width: 1024, height: 1024, prompt: "In the style of TOK, Cute police dog", 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: 26 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun nandycc/sdxl-mascot-avatars using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nandycc/sdxl-mascot-avatars:f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", input={ "width": 1024, "height": 1024, "prompt": "In the style of TOK, Cute police dog", "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": 26 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run nandycc/sdxl-mascot-avatars 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": "f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", "input": { "width": 1024, "height": 1024, "prompt": "In the style of TOK, Cute police dog", "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": 26 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-27T12:09:43.723926Z", "created_at": "2023-09-27T12:09:34.931340Z", "data_removed": false, "error": null, "id": "6cj36ytbc2b3jbghudm23vfszi", "input": { "width": 1024, "height": 1024, "prompt": "In the style of TOK, Cute police dog", "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": 26 }, "logs": "Using seed: 4144\nPrompt: In the style of <s0><s1>, Cute police dog\ntxt2img mode\n 0%| | 0/26 [00:00<?, ?it/s]\n 4%|▍ | 1/26 [00:00<00:06, 3.74it/s]\n 8%|▊ | 2/26 [00:00<00:06, 3.72it/s]\n 12%|█▏ | 3/26 [00:00<00:06, 3.71it/s]\n 15%|█▌ | 4/26 [00:01<00:05, 3.70it/s]\n 19%|█▉ | 5/26 [00:01<00:05, 3.70it/s]\n 23%|██▎ | 6/26 [00:01<00:05, 3.70it/s]\n 27%|██▋ | 7/26 [00:01<00:05, 3.70it/s]\n 31%|███ | 8/26 [00:02<00:04, 3.69it/s]\n 35%|███▍ | 9/26 [00:02<00:04, 3.70it/s]\n 38%|███▊ | 10/26 [00:02<00:04, 3.70it/s]\n 42%|████▏ | 11/26 [00:02<00:04, 3.70it/s]\n 46%|████▌ | 12/26 [00:03<00:03, 3.71it/s]\n 50%|█████ | 13/26 [00:03<00:03, 3.71it/s]\n 54%|█████▍ | 14/26 [00:03<00:03, 3.71it/s]\n 58%|█████▊ | 15/26 [00:04<00:02, 3.71it/s]\n 62%|██████▏ | 16/26 [00:04<00:02, 3.71it/s]\n 65%|██████▌ | 17/26 [00:04<00:02, 3.71it/s]\n 69%|██████▉ | 18/26 [00:04<00:02, 3.70it/s]\n 73%|███████▎ | 19/26 [00:05<00:01, 3.71it/s]\n 77%|███████▋ | 20/26 [00:05<00:01, 3.71it/s]\n 81%|████████ | 21/26 [00:05<00:01, 3.71it/s]\n 85%|████████▍ | 22/26 [00:05<00:01, 3.70it/s]\n 88%|████████▊ | 23/26 [00:06<00:00, 3.71it/s]\n 92%|█████████▏| 24/26 [00:06<00:00, 3.71it/s]\n 96%|█████████▌| 25/26 [00:06<00:00, 3.71it/s]\n100%|██████████| 26/26 [00:07<00:00, 3.70it/s]\n100%|██████████| 26/26 [00:07<00:00, 3.71it/s]", "metrics": { "predict_time": 8.796761, "total_time": 8.792586 }, "output": [ "https://pbxt.replicate.delivery/8e3k5FLbGiw2bankhv6hI4gimHk6d3SuMEzRFqg7xnSDbO0IA/out-0.png" ], "started_at": "2023-09-27T12:09:34.927165Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/6cj36ytbc2b3jbghudm23vfszi", "cancel": "https://api.replicate.com/v1/predictions/6cj36ytbc2b3jbghudm23vfszi/cancel" }, "version": "f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294" }Generated inUsing seed: 4144 Prompt: In the style of <s0><s1>, Cute police dog txt2img mode 0%| | 0/26 [00:00<?, ?it/s] 4%|▍ | 1/26 [00:00<00:06, 3.74it/s] 8%|▊ | 2/26 [00:00<00:06, 3.72it/s] 12%|█▏ | 3/26 [00:00<00:06, 3.71it/s] 15%|█▌ | 4/26 [00:01<00:05, 3.70it/s] 19%|█▉ | 5/26 [00:01<00:05, 3.70it/s] 23%|██▎ | 6/26 [00:01<00:05, 3.70it/s] 27%|██▋ | 7/26 [00:01<00:05, 3.70it/s] 31%|███ | 8/26 [00:02<00:04, 3.69it/s] 35%|███▍ | 9/26 [00:02<00:04, 3.70it/s] 38%|███▊ | 10/26 [00:02<00:04, 3.70it/s] 42%|████▏ | 11/26 [00:02<00:04, 3.70it/s] 46%|████▌ | 12/26 [00:03<00:03, 3.71it/s] 50%|█████ | 13/26 [00:03<00:03, 3.71it/s] 54%|█████▍ | 14/26 [00:03<00:03, 3.71it/s] 58%|█████▊ | 15/26 [00:04<00:02, 3.71it/s] 62%|██████▏ | 16/26 [00:04<00:02, 3.71it/s] 65%|██████▌ | 17/26 [00:04<00:02, 3.71it/s] 69%|██████▉ | 18/26 [00:04<00:02, 3.70it/s] 73%|███████▎ | 19/26 [00:05<00:01, 3.71it/s] 77%|███████▋ | 20/26 [00:05<00:01, 3.71it/s] 81%|████████ | 21/26 [00:05<00:01, 3.71it/s] 85%|████████▍ | 22/26 [00:05<00:01, 3.70it/s] 88%|████████▊ | 23/26 [00:06<00:00, 3.71it/s] 92%|█████████▏| 24/26 [00:06<00:00, 3.71it/s] 96%|█████████▌| 25/26 [00:06<00:00, 3.71it/s] 100%|██████████| 26/26 [00:07<00:00, 3.70it/s] 100%|██████████| 26/26 [00:07<00:00, 3.71it/s]Prediction
nandycc/sdxl-mascot-avatars:f0f8a157IDj4sfudlbshkzwy2d67b6f6j2aiStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of TOK, Cute cook panda, closeup
- 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
- 40
{ "width": 1024, "height": 1024, "prompt": "In the style of TOK, Cute cook panda, closeup", "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": 40 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run nandycc/sdxl-mascot-avatars using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nandycc/sdxl-mascot-avatars:f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", { input: { width: 1024, height: 1024, prompt: "In the style of TOK, Cute cook panda, closeup", 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: 40 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun nandycc/sdxl-mascot-avatars using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nandycc/sdxl-mascot-avatars:f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", input={ "width": 1024, "height": 1024, "prompt": "In the style of TOK, Cute cook panda, closeup", "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": 40 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run nandycc/sdxl-mascot-avatars 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": "f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", "input": { "width": 1024, "height": 1024, "prompt": "In the style of TOK, Cute cook panda, closeup", "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": 40 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-27T12:12:06.575285Z", "created_at": "2023-09-27T12:11:54.008911Z", "data_removed": false, "error": null, "id": "j4sfudlbshkzwy2d67b6f6j2ai", "input": { "width": 1024, "height": 1024, "prompt": "In the style of TOK, Cute cook panda, closeup", "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": 40 }, "logs": "Using seed: 33440\nPrompt: In the style of <s0><s1>, Cute cook panda, closeup\ntxt2img mode\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:10, 3.74it/s]\n 5%|▌ | 2/40 [00:00<00:10, 3.72it/s]\n 8%|▊ | 3/40 [00:00<00:09, 3.71it/s]\n 10%|█ | 4/40 [00:01<00:09, 3.70it/s]\n 12%|█▎ | 5/40 [00:01<00:09, 3.70it/s]\n 15%|█▌ | 6/40 [00:01<00:09, 3.70it/s]\n 18%|█▊ | 7/40 [00:01<00:08, 3.70it/s]\n 20%|██ | 8/40 [00:02<00:08, 3.70it/s]\n 22%|██▎ | 9/40 [00:02<00:08, 3.70it/s]\n 25%|██▌ | 10/40 [00:02<00:08, 3.70it/s]\n 28%|██▊ | 11/40 [00:02<00:07, 3.70it/s]\n 30%|███ | 12/40 [00:03<00:07, 3.70it/s]\n 32%|███▎ | 13/40 [00:03<00:07, 3.71it/s]\n 35%|███▌ | 14/40 [00:03<00:07, 3.71it/s]\n 38%|███▊ | 15/40 [00:04<00:06, 3.71it/s]\n 40%|████ | 16/40 [00:04<00:06, 3.71it/s]\n 42%|████▎ | 17/40 [00:04<00:06, 3.71it/s]\n 45%|████▌ | 18/40 [00:04<00:05, 3.71it/s]\n 48%|████▊ | 19/40 [00:05<00:05, 3.71it/s]\n 50%|█████ | 20/40 [00:05<00:05, 3.71it/s]\n 52%|█████▎ | 21/40 [00:05<00:05, 3.71it/s]\n 55%|█████▌ | 22/40 [00:05<00:04, 3.71it/s]\n 57%|█████▊ | 23/40 [00:06<00:04, 3.71it/s]\n 60%|██████ | 24/40 [00:06<00:04, 3.71it/s]\n 62%|██████▎ | 25/40 [00:06<00:04, 3.71it/s]\n 65%|██████▌ | 26/40 [00:07<00:03, 3.71it/s]\n 68%|██████▊ | 27/40 [00:07<00:03, 3.71it/s]\n 70%|███████ | 28/40 [00:07<00:03, 3.71it/s]\n 72%|███████▎ | 29/40 [00:07<00:02, 3.71it/s]\n 75%|███████▌ | 30/40 [00:08<00:02, 3.71it/s]\n 78%|███████▊ | 31/40 [00:08<00:02, 3.71it/s]\n 80%|████████ | 32/40 [00:08<00:02, 3.71it/s]\n 82%|████████▎ | 33/40 [00:08<00:01, 3.70it/s]\n 85%|████████▌ | 34/40 [00:09<00:01, 3.70it/s]\n 88%|████████▊ | 35/40 [00:09<00:01, 3.70it/s]\n 90%|█████████ | 36/40 [00:09<00:01, 3.70it/s]\n 92%|█████████▎| 37/40 [00:09<00:00, 3.70it/s]\n 95%|█████████▌| 38/40 [00:10<00:00, 3.70it/s]\n 98%|█████████▊| 39/40 [00:10<00:00, 3.70it/s]\n100%|██████████| 40/40 [00:10<00:00, 3.70it/s]\n100%|██████████| 40/40 [00:10<00:00, 3.71it/s]", "metrics": { "predict_time": 12.581152, "total_time": 12.566374 }, "output": [ "https://pbxt.replicate.delivery/glHCgh2c7kJwNZYM9rLoF8DjWKkBPn9yPVUGBvZgJNZFOHaE/out-0.png" ], "started_at": "2023-09-27T12:11:53.994133Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/j4sfudlbshkzwy2d67b6f6j2ai", "cancel": "https://api.replicate.com/v1/predictions/j4sfudlbshkzwy2d67b6f6j2ai/cancel" }, "version": "f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294" }Generated inUsing seed: 33440 Prompt: In the style of <s0><s1>, Cute cook panda, closeup txt2img mode 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:10, 3.74it/s] 5%|▌ | 2/40 [00:00<00:10, 3.72it/s] 8%|▊ | 3/40 [00:00<00:09, 3.71it/s] 10%|█ | 4/40 [00:01<00:09, 3.70it/s] 12%|█▎ | 5/40 [00:01<00:09, 3.70it/s] 15%|█▌ | 6/40 [00:01<00:09, 3.70it/s] 18%|█▊ | 7/40 [00:01<00:08, 3.70it/s] 20%|██ | 8/40 [00:02<00:08, 3.70it/s] 22%|██▎ | 9/40 [00:02<00:08, 3.70it/s] 25%|██▌ | 10/40 [00:02<00:08, 3.70it/s] 28%|██▊ | 11/40 [00:02<00:07, 3.70it/s] 30%|███ | 12/40 [00:03<00:07, 3.70it/s] 32%|███▎ | 13/40 [00:03<00:07, 3.71it/s] 35%|███▌ | 14/40 [00:03<00:07, 3.71it/s] 38%|███▊ | 15/40 [00:04<00:06, 3.71it/s] 40%|████ | 16/40 [00:04<00:06, 3.71it/s] 42%|████▎ | 17/40 [00:04<00:06, 3.71it/s] 45%|████▌ | 18/40 [00:04<00:05, 3.71it/s] 48%|████▊ | 19/40 [00:05<00:05, 3.71it/s] 50%|█████ | 20/40 [00:05<00:05, 3.71it/s] 52%|█████▎ | 21/40 [00:05<00:05, 3.71it/s] 55%|█████▌ | 22/40 [00:05<00:04, 3.71it/s] 57%|█████▊ | 23/40 [00:06<00:04, 3.71it/s] 60%|██████ | 24/40 [00:06<00:04, 3.71it/s] 62%|██████▎ | 25/40 [00:06<00:04, 3.71it/s] 65%|██████▌ | 26/40 [00:07<00:03, 3.71it/s] 68%|██████▊ | 27/40 [00:07<00:03, 3.71it/s] 70%|███████ | 28/40 [00:07<00:03, 3.71it/s] 72%|███████▎ | 29/40 [00:07<00:02, 3.71it/s] 75%|███████▌ | 30/40 [00:08<00:02, 3.71it/s] 78%|███████▊ | 31/40 [00:08<00:02, 3.71it/s] 80%|████████ | 32/40 [00:08<00:02, 3.71it/s] 82%|████████▎ | 33/40 [00:08<00:01, 3.70it/s] 85%|████████▌ | 34/40 [00:09<00:01, 3.70it/s] 88%|████████▊ | 35/40 [00:09<00:01, 3.70it/s] 90%|█████████ | 36/40 [00:09<00:01, 3.70it/s] 92%|█████████▎| 37/40 [00:09<00:00, 3.70it/s] 95%|█████████▌| 38/40 [00:10<00:00, 3.70it/s] 98%|█████████▊| 39/40 [00:10<00:00, 3.70it/s] 100%|██████████| 40/40 [00:10<00:00, 3.70it/s] 100%|██████████| 40/40 [00:10<00:00, 3.71it/s]Prediction
nandycc/sdxl-mascot-avatars:f0f8a157ID6gegoi3bavkeggjpujiknmipeyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of TOK, Cute giraffe in superhero suit
- 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
- 40
{ "width": 1024, "height": 1024, "prompt": "In the style of TOK, Cute giraffe in superhero suit", "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": 40 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run nandycc/sdxl-mascot-avatars using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nandycc/sdxl-mascot-avatars:f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", { input: { width: 1024, height: 1024, prompt: "In the style of TOK, Cute giraffe in superhero suit", 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: 40 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun nandycc/sdxl-mascot-avatars using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nandycc/sdxl-mascot-avatars:f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", input={ "width": 1024, "height": 1024, "prompt": "In the style of TOK, Cute giraffe in superhero suit", "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": 40 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run nandycc/sdxl-mascot-avatars 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": "f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", "input": { "width": 1024, "height": 1024, "prompt": "In the style of TOK, Cute giraffe in superhero suit", "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": 40 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-27T12:14:17.716475Z", "created_at": "2023-09-27T12:14:01.502615Z", "data_removed": false, "error": null, "id": "6gegoi3bavkeggjpujiknmipey", "input": { "width": 1024, "height": 1024, "prompt": "In the style of TOK, Cute giraffe in superhero suit", "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": 40 }, "logs": "Using seed: 36164\nPrompt: In the style of <s0><s1>, Cute giraffe in superhero suit\ntxt2img mode\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:10, 3.74it/s]\n 5%|▌ | 2/40 [00:00<00:10, 3.72it/s]\n 8%|▊ | 3/40 [00:00<00:09, 3.72it/s]\n 10%|█ | 4/40 [00:01<00:09, 3.70it/s]\n 12%|█▎ | 5/40 [00:01<00:09, 3.70it/s]\n 15%|█▌ | 6/40 [00:01<00:09, 3.70it/s]\n 18%|█▊ | 7/40 [00:01<00:08, 3.70it/s]\n 20%|██ | 8/40 [00:02<00:08, 3.69it/s]\n 22%|██▎ | 9/40 [00:02<00:08, 3.70it/s]\n 25%|██▌ | 10/40 [00:02<00:08, 3.69it/s]\n 28%|██▊ | 11/40 [00:02<00:07, 3.69it/s]\n 30%|███ | 12/40 [00:03<00:07, 3.68it/s]\n 32%|███▎ | 13/40 [00:03<00:07, 3.69it/s]\n 35%|███▌ | 14/40 [00:03<00:07, 3.69it/s]\n 38%|███▊ | 15/40 [00:04<00:06, 3.68it/s]\n 40%|████ | 16/40 [00:04<00:06, 3.68it/s]\n 42%|████▎ | 17/40 [00:04<00:06, 3.68it/s]\n 45%|████▌ | 18/40 [00:04<00:05, 3.68it/s]\n 48%|████▊ | 19/40 [00:05<00:05, 3.68it/s]\n 50%|█████ | 20/40 [00:05<00:05, 3.68it/s]\n 52%|█████▎ | 21/40 [00:05<00:05, 3.68it/s]\n 55%|█████▌ | 22/40 [00:05<00:04, 3.68it/s]\n 57%|█████▊ | 23/40 [00:06<00:04, 3.68it/s]\n 60%|██████ | 24/40 [00:06<00:04, 3.68it/s]\n 62%|██████▎ | 25/40 [00:06<00:04, 3.69it/s]\n 65%|██████▌ | 26/40 [00:07<00:03, 3.69it/s]\n 68%|██████▊ | 27/40 [00:07<00:03, 3.69it/s]\n 70%|███████ | 28/40 [00:07<00:03, 3.69it/s]\n 72%|███████▎ | 29/40 [00:07<00:02, 3.69it/s]\n 75%|███████▌ | 30/40 [00:08<00:02, 3.68it/s]\n 78%|███████▊ | 31/40 [00:08<00:02, 3.68it/s]\n 80%|████████ | 32/40 [00:08<00:02, 3.69it/s]\n 82%|████████▎ | 33/40 [00:08<00:01, 3.68it/s]\n 85%|████████▌ | 34/40 [00:09<00:01, 3.68it/s]\n 88%|████████▊ | 35/40 [00:09<00:01, 3.68it/s]\n 90%|█████████ | 36/40 [00:09<00:01, 3.68it/s]\n 92%|█████████▎| 37/40 [00:10<00:00, 3.68it/s]\n 95%|█████████▌| 38/40 [00:10<00:00, 3.68it/s]\n 98%|█████████▊| 39/40 [00:10<00:00, 3.67it/s]\n100%|██████████| 40/40 [00:10<00:00, 3.67it/s]\n100%|██████████| 40/40 [00:10<00:00, 3.69it/s]", "metrics": { "predict_time": 12.641943, "total_time": 16.21386 }, "output": [ "https://pbxt.replicate.delivery/ugoVU3h9CzKJMFt9VJHvrBYJI1OfgjkpRrgPaEVAokGMdO0IA/out-0.png" ], "started_at": "2023-09-27T12:14:05.074532Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/6gegoi3bavkeggjpujiknmipey", "cancel": "https://api.replicate.com/v1/predictions/6gegoi3bavkeggjpujiknmipey/cancel" }, "version": "f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294" }Generated inUsing seed: 36164 Prompt: In the style of <s0><s1>, Cute giraffe in superhero suit txt2img mode 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:10, 3.74it/s] 5%|▌ | 2/40 [00:00<00:10, 3.72it/s] 8%|▊ | 3/40 [00:00<00:09, 3.72it/s] 10%|█ | 4/40 [00:01<00:09, 3.70it/s] 12%|█▎ | 5/40 [00:01<00:09, 3.70it/s] 15%|█▌ | 6/40 [00:01<00:09, 3.70it/s] 18%|█▊ | 7/40 [00:01<00:08, 3.70it/s] 20%|██ | 8/40 [00:02<00:08, 3.69it/s] 22%|██▎ | 9/40 [00:02<00:08, 3.70it/s] 25%|██▌ | 10/40 [00:02<00:08, 3.69it/s] 28%|██▊ | 11/40 [00:02<00:07, 3.69it/s] 30%|███ | 12/40 [00:03<00:07, 3.68it/s] 32%|███▎ | 13/40 [00:03<00:07, 3.69it/s] 35%|███▌ | 14/40 [00:03<00:07, 3.69it/s] 38%|███▊ | 15/40 [00:04<00:06, 3.68it/s] 40%|████ | 16/40 [00:04<00:06, 3.68it/s] 42%|████▎ | 17/40 [00:04<00:06, 3.68it/s] 45%|████▌ | 18/40 [00:04<00:05, 3.68it/s] 48%|████▊ | 19/40 [00:05<00:05, 3.68it/s] 50%|█████ | 20/40 [00:05<00:05, 3.68it/s] 52%|█████▎ | 21/40 [00:05<00:05, 3.68it/s] 55%|█████▌ | 22/40 [00:05<00:04, 3.68it/s] 57%|█████▊ | 23/40 [00:06<00:04, 3.68it/s] 60%|██████ | 24/40 [00:06<00:04, 3.68it/s] 62%|██████▎ | 25/40 [00:06<00:04, 3.69it/s] 65%|██████▌ | 26/40 [00:07<00:03, 3.69it/s] 68%|██████▊ | 27/40 [00:07<00:03, 3.69it/s] 70%|███████ | 28/40 [00:07<00:03, 3.69it/s] 72%|███████▎ | 29/40 [00:07<00:02, 3.69it/s] 75%|███████▌ | 30/40 [00:08<00:02, 3.68it/s] 78%|███████▊ | 31/40 [00:08<00:02, 3.68it/s] 80%|████████ | 32/40 [00:08<00:02, 3.69it/s] 82%|████████▎ | 33/40 [00:08<00:01, 3.68it/s] 85%|████████▌ | 34/40 [00:09<00:01, 3.68it/s] 88%|████████▊ | 35/40 [00:09<00:01, 3.68it/s] 90%|█████████ | 36/40 [00:09<00:01, 3.68it/s] 92%|█████████▎| 37/40 [00:10<00:00, 3.68it/s] 95%|█████████▌| 38/40 [00:10<00:00, 3.68it/s] 98%|█████████▊| 39/40 [00:10<00:00, 3.67it/s] 100%|██████████| 40/40 [00:10<00:00, 3.67it/s] 100%|██████████| 40/40 [00:10<00:00, 3.69it/s]Prediction
nandycc/sdxl-mascot-avatars:f0f8a157IDgfw34i3b6iuc46bqyo6vzk766eStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of TOK, Cute detective platypus, with magnifying glass in hand
- 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
- 40
{ "width": 1024, "height": 1024, "prompt": "In the style of TOK, Cute detective platypus, with magnifying glass in hand", "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": 40 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run nandycc/sdxl-mascot-avatars using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nandycc/sdxl-mascot-avatars:f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", { input: { width: 1024, height: 1024, prompt: "In the style of TOK, Cute detective platypus, with magnifying glass in hand", 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: 40 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun nandycc/sdxl-mascot-avatars using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nandycc/sdxl-mascot-avatars:f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", input={ "width": 1024, "height": 1024, "prompt": "In the style of TOK, Cute detective platypus, with magnifying glass in hand", "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": 40 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run nandycc/sdxl-mascot-avatars 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": "f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", "input": { "width": 1024, "height": 1024, "prompt": "In the style of TOK, Cute detective platypus, with magnifying glass in hand", "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": 40 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-27T12:23:07.328991Z", "created_at": "2023-09-27T12:22:54.793962Z", "data_removed": false, "error": null, "id": "gfw34i3b6iuc46bqyo6vzk766e", "input": { "width": 1024, "height": 1024, "prompt": "In the style of TOK, Cute detective platypus, with magnifying glass in hand", "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": 40 }, "logs": "Using seed: 8060\nPrompt: In the style of <s0><s1>, Cute detective platypus, with magnifying glass in hand\ntxt2img mode\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:10, 3.73it/s]\n 5%|▌ | 2/40 [00:00<00:10, 3.72it/s]\n 8%|▊ | 3/40 [00:00<00:09, 3.71it/s]\n 10%|█ | 4/40 [00:01<00:09, 3.69it/s]\n 12%|█▎ | 5/40 [00:01<00:09, 3.69it/s]\n 15%|█▌ | 6/40 [00:01<00:09, 3.69it/s]\n 18%|█▊ | 7/40 [00:01<00:08, 3.69it/s]\n 20%|██ | 8/40 [00:02<00:08, 3.68it/s]\n 22%|██▎ | 9/40 [00:02<00:08, 3.68it/s]\n 25%|██▌ | 10/40 [00:02<00:08, 3.69it/s]\n 28%|██▊ | 11/40 [00:02<00:07, 3.70it/s]\n 30%|███ | 12/40 [00:03<00:07, 3.69it/s]\n 32%|███▎ | 13/40 [00:03<00:07, 3.70it/s]\n 35%|███▌ | 14/40 [00:03<00:07, 3.70it/s]\n 38%|███▊ | 15/40 [00:04<00:06, 3.70it/s]\n 40%|████ | 16/40 [00:04<00:06, 3.70it/s]\n 42%|████▎ | 17/40 [00:04<00:06, 3.70it/s]\n 45%|████▌ | 18/40 [00:04<00:05, 3.70it/s]\n 48%|████▊ | 19/40 [00:05<00:05, 3.70it/s]\n 50%|█████ | 20/40 [00:05<00:05, 3.70it/s]\n 52%|█████▎ | 21/40 [00:05<00:05, 3.70it/s]\n 55%|█████▌ | 22/40 [00:05<00:04, 3.70it/s]\n 57%|█████▊ | 23/40 [00:06<00:04, 3.70it/s]\n 60%|██████ | 24/40 [00:06<00:04, 3.70it/s]\n 62%|██████▎ | 25/40 [00:06<00:04, 3.70it/s]\n 65%|██████▌ | 26/40 [00:07<00:03, 3.70it/s]\n 68%|██████▊ | 27/40 [00:07<00:03, 3.70it/s]\n 70%|███████ | 28/40 [00:07<00:03, 3.70it/s]\n 72%|███████▎ | 29/40 [00:07<00:02, 3.70it/s]\n 75%|███████▌ | 30/40 [00:08<00:02, 3.70it/s]\n 78%|███████▊ | 31/40 [00:08<00:02, 3.69it/s]\n 80%|████████ | 32/40 [00:08<00:02, 3.69it/s]\n 82%|████████▎ | 33/40 [00:08<00:01, 3.70it/s]\n 85%|████████▌ | 34/40 [00:09<00:01, 3.69it/s]\n 88%|████████▊ | 35/40 [00:09<00:01, 3.69it/s]\n 90%|█████████ | 36/40 [00:09<00:01, 3.69it/s]\n 92%|█████████▎| 37/40 [00:10<00:00, 3.69it/s]\n 95%|█████████▌| 38/40 [00:10<00:00, 3.69it/s]\n 98%|█████████▊| 39/40 [00:10<00:00, 3.69it/s]\n100%|██████████| 40/40 [00:10<00:00, 3.69it/s]\n100%|██████████| 40/40 [00:10<00:00, 3.70it/s]", "metrics": { "predict_time": 12.547685, "total_time": 12.535029 }, "output": [ "https://pbxt.replicate.delivery/QWUTNFUzN9YWPhnxMi1TTtVeKnfqautNcIE5mSbExixqCdoRA/out-0.png" ], "started_at": "2023-09-27T12:22:54.781306Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/gfw34i3b6iuc46bqyo6vzk766e", "cancel": "https://api.replicate.com/v1/predictions/gfw34i3b6iuc46bqyo6vzk766e/cancel" }, "version": "f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294" }Generated inUsing seed: 8060 Prompt: In the style of <s0><s1>, Cute detective platypus, with magnifying glass in hand txt2img mode 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:10, 3.73it/s] 5%|▌ | 2/40 [00:00<00:10, 3.72it/s] 8%|▊ | 3/40 [00:00<00:09, 3.71it/s] 10%|█ | 4/40 [00:01<00:09, 3.69it/s] 12%|█▎ | 5/40 [00:01<00:09, 3.69it/s] 15%|█▌ | 6/40 [00:01<00:09, 3.69it/s] 18%|█▊ | 7/40 [00:01<00:08, 3.69it/s] 20%|██ | 8/40 [00:02<00:08, 3.68it/s] 22%|██▎ | 9/40 [00:02<00:08, 3.68it/s] 25%|██▌ | 10/40 [00:02<00:08, 3.69it/s] 28%|██▊ | 11/40 [00:02<00:07, 3.70it/s] 30%|███ | 12/40 [00:03<00:07, 3.69it/s] 32%|███▎ | 13/40 [00:03<00:07, 3.70it/s] 35%|███▌ | 14/40 [00:03<00:07, 3.70it/s] 38%|███▊ | 15/40 [00:04<00:06, 3.70it/s] 40%|████ | 16/40 [00:04<00:06, 3.70it/s] 42%|████▎ | 17/40 [00:04<00:06, 3.70it/s] 45%|████▌ | 18/40 [00:04<00:05, 3.70it/s] 48%|████▊ | 19/40 [00:05<00:05, 3.70it/s] 50%|█████ | 20/40 [00:05<00:05, 3.70it/s] 52%|█████▎ | 21/40 [00:05<00:05, 3.70it/s] 55%|█████▌ | 22/40 [00:05<00:04, 3.70it/s] 57%|█████▊ | 23/40 [00:06<00:04, 3.70it/s] 60%|██████ | 24/40 [00:06<00:04, 3.70it/s] 62%|██████▎ | 25/40 [00:06<00:04, 3.70it/s] 65%|██████▌ | 26/40 [00:07<00:03, 3.70it/s] 68%|██████▊ | 27/40 [00:07<00:03, 3.70it/s] 70%|███████ | 28/40 [00:07<00:03, 3.70it/s] 72%|███████▎ | 29/40 [00:07<00:02, 3.70it/s] 75%|███████▌ | 30/40 [00:08<00:02, 3.70it/s] 78%|███████▊ | 31/40 [00:08<00:02, 3.69it/s] 80%|████████ | 32/40 [00:08<00:02, 3.69it/s] 82%|████████▎ | 33/40 [00:08<00:01, 3.70it/s] 85%|████████▌ | 34/40 [00:09<00:01, 3.69it/s] 88%|████████▊ | 35/40 [00:09<00:01, 3.69it/s] 90%|█████████ | 36/40 [00:09<00:01, 3.69it/s] 92%|█████████▎| 37/40 [00:10<00:00, 3.69it/s] 95%|█████████▌| 38/40 [00:10<00:00, 3.69it/s] 98%|█████████▊| 39/40 [00:10<00:00, 3.69it/s] 100%|██████████| 40/40 [00:10<00:00, 3.69it/s] 100%|██████████| 40/40 [00:10<00:00, 3.70it/s]Prediction
nandycc/sdxl-mascot-avatars:f0f8a157IDy64hkb3bwrckjozw7li34cnqhuStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedby @nandyccInput
- width
- 1024
- height
- 1024
- prompt
- In the style of TOK, body builder Trex, lifting weights
- 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
- 40
{ "width": 1024, "height": 1024, "prompt": "In the style of TOK, body builder Trex, lifting weights ", "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": 40 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run nandycc/sdxl-mascot-avatars using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nandycc/sdxl-mascot-avatars:f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", { input: { width: 1024, height: 1024, prompt: "In the style of TOK, body builder Trex, lifting weights ", 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: 40 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun nandycc/sdxl-mascot-avatars using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nandycc/sdxl-mascot-avatars:f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", input={ "width": 1024, "height": 1024, "prompt": "In the style of TOK, body builder Trex, lifting weights ", "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": 40 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run nandycc/sdxl-mascot-avatars 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": "f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", "input": { "width": 1024, "height": 1024, "prompt": "In the style of TOK, body builder Trex, lifting weights ", "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": 40 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-27T12:28:17.097727Z", "created_at": "2023-09-27T12:28:04.503157Z", "data_removed": false, "error": null, "id": "y64hkb3bwrckjozw7li34cnqhu", "input": { "width": 1024, "height": 1024, "prompt": "In the style of TOK, body builder Trex, lifting weights ", "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": 40 }, "logs": "Using seed: 54476\nPrompt: In the style of <s0><s1>, body builder Trex, lifting weights\ntxt2img mode\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:10, 3.72it/s]\n 5%|▌ | 2/40 [00:00<00:10, 3.71it/s]\n 8%|▊ | 3/40 [00:00<00:09, 3.71it/s]\n 10%|█ | 4/40 [00:01<00:09, 3.69it/s]\n 12%|█▎ | 5/40 [00:01<00:09, 3.69it/s]\n 15%|█▌ | 6/40 [00:01<00:09, 3.69it/s]\n 18%|█▊ | 7/40 [00:01<00:08, 3.69it/s]\n 20%|██ | 8/40 [00:02<00:08, 3.68it/s]\n 22%|██▎ | 9/40 [00:02<00:08, 3.68it/s]\n 25%|██▌ | 10/40 [00:02<00:08, 3.69it/s]\n 28%|██▊ | 11/40 [00:02<00:07, 3.68it/s]\n 30%|███ | 12/40 [00:03<00:07, 3.68it/s]\n 32%|███▎ | 13/40 [00:03<00:07, 3.68it/s]\n 35%|███▌ | 14/40 [00:03<00:07, 3.69it/s]\n 38%|███▊ | 15/40 [00:04<00:06, 3.69it/s]\n 40%|████ | 16/40 [00:04<00:06, 3.69it/s]\n 42%|████▎ | 17/40 [00:04<00:06, 3.70it/s]\n 45%|████▌ | 18/40 [00:04<00:05, 3.70it/s]\n 48%|████▊ | 19/40 [00:05<00:05, 3.70it/s]\n 50%|█████ | 20/40 [00:05<00:05, 3.70it/s]\n 52%|█████▎ | 21/40 [00:05<00:05, 3.70it/s]\n 55%|█████▌ | 22/40 [00:05<00:04, 3.70it/s]\n 57%|█████▊ | 23/40 [00:06<00:04, 3.70it/s]\n 60%|██████ | 24/40 [00:06<00:04, 3.70it/s]\n 62%|██████▎ | 25/40 [00:06<00:04, 3.70it/s]\n 65%|██████▌ | 26/40 [00:07<00:03, 3.70it/s]\n 68%|██████▊ | 27/40 [00:07<00:03, 3.70it/s]\n 70%|███████ | 28/40 [00:07<00:03, 3.70it/s]\n 72%|███████▎ | 29/40 [00:07<00:02, 3.70it/s]\n 75%|███████▌ | 30/40 [00:08<00:02, 3.70it/s]\n 78%|███████▊ | 31/40 [00:08<00:02, 3.70it/s]\n 80%|████████ | 32/40 [00:08<00:02, 3.70it/s]\n 82%|████████▎ | 33/40 [00:08<00:01, 3.70it/s]\n 85%|████████▌ | 34/40 [00:09<00:01, 3.70it/s]\n 88%|████████▊ | 35/40 [00:09<00:01, 3.70it/s]\n 90%|█████████ | 36/40 [00:09<00:01, 3.70it/s]\n 92%|█████████▎| 37/40 [00:10<00:00, 3.69it/s]\n 95%|█████████▌| 38/40 [00:10<00:00, 3.69it/s]\n 98%|█████████▊| 39/40 [00:10<00:00, 3.69it/s]\n100%|██████████| 40/40 [00:10<00:00, 3.70it/s]\n100%|██████████| 40/40 [00:10<00:00, 3.70it/s]", "metrics": { "predict_time": 12.606188, "total_time": 12.59457 }, "output": [ "https://pbxt.replicate.delivery/XDGmqYizf6VHcCGSe7ei3JsxmgGVZZ98WV15GELYqAbAP6QjA/out-0.png" ], "started_at": "2023-09-27T12:28:04.491539Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/y64hkb3bwrckjozw7li34cnqhu", "cancel": "https://api.replicate.com/v1/predictions/y64hkb3bwrckjozw7li34cnqhu/cancel" }, "version": "f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294" }Generated inUsing seed: 54476 Prompt: In the style of <s0><s1>, body builder Trex, lifting weights txt2img mode 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:10, 3.72it/s] 5%|▌ | 2/40 [00:00<00:10, 3.71it/s] 8%|▊ | 3/40 [00:00<00:09, 3.71it/s] 10%|█ | 4/40 [00:01<00:09, 3.69it/s] 12%|█▎ | 5/40 [00:01<00:09, 3.69it/s] 15%|█▌ | 6/40 [00:01<00:09, 3.69it/s] 18%|█▊ | 7/40 [00:01<00:08, 3.69it/s] 20%|██ | 8/40 [00:02<00:08, 3.68it/s] 22%|██▎ | 9/40 [00:02<00:08, 3.68it/s] 25%|██▌ | 10/40 [00:02<00:08, 3.69it/s] 28%|██▊ | 11/40 [00:02<00:07, 3.68it/s] 30%|███ | 12/40 [00:03<00:07, 3.68it/s] 32%|███▎ | 13/40 [00:03<00:07, 3.68it/s] 35%|███▌ | 14/40 [00:03<00:07, 3.69it/s] 38%|███▊ | 15/40 [00:04<00:06, 3.69it/s] 40%|████ | 16/40 [00:04<00:06, 3.69it/s] 42%|████▎ | 17/40 [00:04<00:06, 3.70it/s] 45%|████▌ | 18/40 [00:04<00:05, 3.70it/s] 48%|████▊ | 19/40 [00:05<00:05, 3.70it/s] 50%|█████ | 20/40 [00:05<00:05, 3.70it/s] 52%|█████▎ | 21/40 [00:05<00:05, 3.70it/s] 55%|█████▌ | 22/40 [00:05<00:04, 3.70it/s] 57%|█████▊ | 23/40 [00:06<00:04, 3.70it/s] 60%|██████ | 24/40 [00:06<00:04, 3.70it/s] 62%|██████▎ | 25/40 [00:06<00:04, 3.70it/s] 65%|██████▌ | 26/40 [00:07<00:03, 3.70it/s] 68%|██████▊ | 27/40 [00:07<00:03, 3.70it/s] 70%|███████ | 28/40 [00:07<00:03, 3.70it/s] 72%|███████▎ | 29/40 [00:07<00:02, 3.70it/s] 75%|███████▌ | 30/40 [00:08<00:02, 3.70it/s] 78%|███████▊ | 31/40 [00:08<00:02, 3.70it/s] 80%|████████ | 32/40 [00:08<00:02, 3.70it/s] 82%|████████▎ | 33/40 [00:08<00:01, 3.70it/s] 85%|████████▌ | 34/40 [00:09<00:01, 3.70it/s] 88%|████████▊ | 35/40 [00:09<00:01, 3.70it/s] 90%|█████████ | 36/40 [00:09<00:01, 3.70it/s] 92%|█████████▎| 37/40 [00:10<00:00, 3.69it/s] 95%|█████████▌| 38/40 [00:10<00:00, 3.69it/s] 98%|█████████▊| 39/40 [00:10<00:00, 3.69it/s] 100%|██████████| 40/40 [00:10<00:00, 3.70it/s] 100%|██████████| 40/40 [00:10<00:00, 3.70it/s]Prediction
nandycc/sdxl-mascot-avatars:f0f8a157IDt6wvjglbo2xzv2fmon2c6givuuStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- In the style of TOK, rapper dog, gold chain , black outfit, rugged look, closeup
- 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
- 0.59
- num_inference_steps
- 40
{ "width": 1024, "height": 1024, "prompt": "In the style of TOK, rapper dog, gold chain , black outfit, rugged look, closeup", "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": 0.59, "num_inference_steps": 40 }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run nandycc/sdxl-mascot-avatars using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "nandycc/sdxl-mascot-avatars:f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", { input: { width: 1024, height: 1024, prompt: "In the style of TOK, rapper dog, gold chain , black outfit, rugged look, closeup", 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: 0.59, num_inference_steps: 40 } } ); console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun nandycc/sdxl-mascot-avatars using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "nandycc/sdxl-mascot-avatars:f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", input={ "width": 1024, "height": 1024, "prompt": "In the style of TOK, rapper dog, gold chain , black outfit, rugged look, closeup", "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": 0.59, "num_inference_steps": 40 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run nandycc/sdxl-mascot-avatars 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": "f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294", "input": { "width": 1024, "height": 1024, "prompt": "In the style of TOK, rapper dog, gold chain , black outfit, rugged look, closeup", "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": 0.59, "num_inference_steps": 40 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-28T05:04:49.593462Z", "created_at": "2023-09-28T05:04:36.310169Z", "data_removed": false, "error": null, "id": "t6wvjglbo2xzv2fmon2c6givuu", "input": { "width": 1024, "height": 1024, "prompt": "In the style of TOK, rapper dog, gold chain , black outfit, rugged look, closeup", "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": 0.59, "num_inference_steps": 40 }, "logs": "Using seed: 36114\nPrompt: In the style of <s0><s1>, rapper dog, gold chain , black outfit, rugged look, closeup\ntxt2img mode\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:11, 3.52it/s]\n 5%|▌ | 2/40 [00:00<00:10, 3.51it/s]\n 8%|▊ | 3/40 [00:00<00:10, 3.51it/s]\n 10%|█ | 4/40 [00:01<00:10, 3.50it/s]\n 12%|█▎ | 5/40 [00:01<00:09, 3.50it/s]\n 15%|█▌ | 6/40 [00:01<00:09, 3.50it/s]\n 18%|█▊ | 7/40 [00:01<00:09, 3.50it/s]\n 20%|██ | 8/40 [00:02<00:09, 3.50it/s]\n 22%|██▎ | 9/40 [00:02<00:08, 3.50it/s]\n 25%|██▌ | 10/40 [00:02<00:08, 3.50it/s]\n 28%|██▊ | 11/40 [00:03<00:08, 3.50it/s]\n 30%|███ | 12/40 [00:03<00:08, 3.50it/s]\n 32%|███▎ | 13/40 [00:03<00:07, 3.50it/s]\n 35%|███▌ | 14/40 [00:03<00:07, 3.50it/s]\n 38%|███▊ | 15/40 [00:04<00:07, 3.49it/s]\n 40%|████ | 16/40 [00:04<00:06, 3.49it/s]\n 42%|████▎ | 17/40 [00:04<00:06, 3.49it/s]\n 45%|████▌ | 18/40 [00:05<00:06, 3.49it/s]\n 48%|████▊ | 19/40 [00:05<00:06, 3.49it/s]\n 50%|█████ | 20/40 [00:05<00:05, 3.49it/s]\n 52%|█████▎ | 21/40 [00:06<00:05, 3.49it/s]\n 55%|█████▌ | 22/40 [00:06<00:05, 3.49it/s]\n 57%|█████▊ | 23/40 [00:06<00:04, 3.49it/s]\n 60%|██████ | 24/40 [00:06<00:04, 3.49it/s]\n 62%|██████▎ | 25/40 [00:07<00:04, 3.49it/s]\n 65%|██████▌ | 26/40 [00:07<00:04, 3.49it/s]\n 68%|██████▊ | 27/40 [00:07<00:03, 3.49it/s]\n 70%|███████ | 28/40 [00:08<00:03, 3.49it/s]\n 72%|███████▎ | 29/40 [00:08<00:03, 3.48it/s]\n 75%|███████▌ | 30/40 [00:08<00:02, 3.48it/s]\n 78%|███████▊ | 31/40 [00:08<00:02, 3.48it/s]\n 80%|████████ | 32/40 [00:09<00:02, 3.48it/s]\n 82%|████████▎ | 33/40 [00:09<00:02, 3.48it/s]\n 85%|████████▌ | 34/40 [00:09<00:01, 3.48it/s]\n 88%|████████▊ | 35/40 [00:10<00:01, 3.48it/s]\n 90%|█████████ | 36/40 [00:10<00:01, 3.48it/s]\n 92%|█████████▎| 37/40 [00:10<00:00, 3.48it/s]\n 95%|█████████▌| 38/40 [00:10<00:00, 3.48it/s]\n 98%|█████████▊| 39/40 [00:11<00:00, 3.48it/s]\n100%|██████████| 40/40 [00:11<00:00, 3.48it/s]\n100%|██████████| 40/40 [00:11<00:00, 3.49it/s]", "metrics": { "predict_time": 13.284991, "total_time": 13.283293 }, "output": [ "https://pbxt.replicate.delivery/ejrRikmas8WXMa04i9Zq3Cxne066RSGSWTk419dX1NPwtroRA/out-0.png" ], "started_at": "2023-09-28T05:04:36.308471Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/t6wvjglbo2xzv2fmon2c6givuu", "cancel": "https://api.replicate.com/v1/predictions/t6wvjglbo2xzv2fmon2c6givuu/cancel" }, "version": "f0f8a1578f4e57da2090b1846a3c026bd75d38abd969e1d4788b07f203966294" }Generated inUsing seed: 36114 Prompt: In the style of <s0><s1>, rapper dog, gold chain , black outfit, rugged look, closeup txt2img mode 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:11, 3.52it/s] 5%|▌ | 2/40 [00:00<00:10, 3.51it/s] 8%|▊ | 3/40 [00:00<00:10, 3.51it/s] 10%|█ | 4/40 [00:01<00:10, 3.50it/s] 12%|█▎ | 5/40 [00:01<00:09, 3.50it/s] 15%|█▌ | 6/40 [00:01<00:09, 3.50it/s] 18%|█▊ | 7/40 [00:01<00:09, 3.50it/s] 20%|██ | 8/40 [00:02<00:09, 3.50it/s] 22%|██▎ | 9/40 [00:02<00:08, 3.50it/s] 25%|██▌ | 10/40 [00:02<00:08, 3.50it/s] 28%|██▊ | 11/40 [00:03<00:08, 3.50it/s] 30%|███ | 12/40 [00:03<00:08, 3.50it/s] 32%|███▎ | 13/40 [00:03<00:07, 3.50it/s] 35%|███▌ | 14/40 [00:03<00:07, 3.50it/s] 38%|███▊ | 15/40 [00:04<00:07, 3.49it/s] 40%|████ | 16/40 [00:04<00:06, 3.49it/s] 42%|████▎ | 17/40 [00:04<00:06, 3.49it/s] 45%|████▌ | 18/40 [00:05<00:06, 3.49it/s] 48%|████▊ | 19/40 [00:05<00:06, 3.49it/s] 50%|█████ | 20/40 [00:05<00:05, 3.49it/s] 52%|█████▎ | 21/40 [00:06<00:05, 3.49it/s] 55%|█████▌ | 22/40 [00:06<00:05, 3.49it/s] 57%|█████▊ | 23/40 [00:06<00:04, 3.49it/s] 60%|██████ | 24/40 [00:06<00:04, 3.49it/s] 62%|██████▎ | 25/40 [00:07<00:04, 3.49it/s] 65%|██████▌ | 26/40 [00:07<00:04, 3.49it/s] 68%|██████▊ | 27/40 [00:07<00:03, 3.49it/s] 70%|███████ | 28/40 [00:08<00:03, 3.49it/s] 72%|███████▎ | 29/40 [00:08<00:03, 3.48it/s] 75%|███████▌ | 30/40 [00:08<00:02, 3.48it/s] 78%|███████▊ | 31/40 [00:08<00:02, 3.48it/s] 80%|████████ | 32/40 [00:09<00:02, 3.48it/s] 82%|████████▎ | 33/40 [00:09<00:02, 3.48it/s] 85%|████████▌ | 34/40 [00:09<00:01, 3.48it/s] 88%|████████▊ | 35/40 [00:10<00:01, 3.48it/s] 90%|█████████ | 36/40 [00:10<00:01, 3.48it/s] 92%|█████████▎| 37/40 [00:10<00:00, 3.48it/s] 95%|█████████▌| 38/40 [00:10<00:00, 3.48it/s] 98%|█████████▊| 39/40 [00:11<00:00, 3.48it/s] 100%|██████████| 40/40 [00:11<00:00, 3.48it/s] 100%|██████████| 40/40 [00:11<00:00, 3.49it/s]
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