ghostofpokemon / sdxl-family-guy
Model trained on Family Guy animation style
- Public
- 464 runs
- SDXL fine-tune
Prediction
ghostofpokemon/sdxl-family-guy:6cd71fdb0694e8b04c81882340082864b55b591b4d3b6cb3b949ca2b28592446IDxaztsqtbv2unf526zztmqljtjqStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 3472
- width
- 1280
- height
- 720
- prompt
- animated picture of a single-family house in the style of TOK, clean, simple
- refine
- expert_ensemble_refiner
- scheduler
- DPMSolverMultistep
- lora_scale
- 0.85
- num_outputs
- 4
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.95
- negative_prompt
- underexposed, ugly, broken
- prompt_strength
- 0.81
- num_inference_steps
- 50
{ "seed": 3472, "width": 1280, "height": 720, "prompt": "animated picture of a single-family house in the style of TOK, clean, simple", "refine": "expert_ensemble_refiner", "scheduler": "DPMSolverMultistep", "lora_scale": 0.85, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "underexposed, ugly, broken", "prompt_strength": 0.81, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ghostofpokemon/sdxl-family-guy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ghostofpokemon/sdxl-family-guy:6cd71fdb0694e8b04c81882340082864b55b591b4d3b6cb3b949ca2b28592446", { input: { seed: 3472, width: 1280, height: 720, prompt: "animated picture of a single-family house in the style of TOK, clean, simple", refine: "expert_ensemble_refiner", scheduler: "DPMSolverMultistep", lora_scale: 0.85, num_outputs: 4, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.95, negative_prompt: "underexposed, ugly, broken", prompt_strength: 0.81, 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 replicate
Import the client:import replicate
Run ghostofpokemon/sdxl-family-guy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ghostofpokemon/sdxl-family-guy:6cd71fdb0694e8b04c81882340082864b55b591b4d3b6cb3b949ca2b28592446", input={ "seed": 3472, "width": 1280, "height": 720, "prompt": "animated picture of a single-family house in the style of TOK, clean, simple", "refine": "expert_ensemble_refiner", "scheduler": "DPMSolverMultistep", "lora_scale": 0.85, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.95, "negative_prompt": "underexposed, ugly, broken", "prompt_strength": 0.81, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run ghostofpokemon/sdxl-family-guy 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": "ghostofpokemon/sdxl-family-guy:6cd71fdb0694e8b04c81882340082864b55b591b4d3b6cb3b949ca2b28592446", "input": { "seed": 3472, "width": 1280, "height": 720, "prompt": "animated picture of a single-family house in the style of TOK, clean, simple", "refine": "expert_ensemble_refiner", "scheduler": "DPMSolverMultistep", "lora_scale": 0.85, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "underexposed, ugly, broken", "prompt_strength": 0.81, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-07T09:20:11.064808Z", "created_at": "2023-11-07T09:19:27.371035Z", "data_removed": false, "error": null, "id": "xaztsqtbv2unf526zztmqljtjq", "input": { "seed": 3472, "width": 1280, "height": 720, "prompt": "animated picture of a single-family house in the style of TOK, clean, simple", "refine": "expert_ensemble_refiner", "scheduler": "DPMSolverMultistep", "lora_scale": 0.85, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "underexposed, ugly, broken", "prompt_strength": 0.81, "num_inference_steps": 50 }, "logs": "Using seed: 3472\nPrompt: animated picture of a single-family house in the style of <s0><s1>, clean, simple\ntxt2img mode\n 0%| | 0/38 [00:00<?, ?it/s]\n 3%|▎ | 1/38 [00:00<00:34, 1.07it/s]\n 5%|▌ | 2/38 [00:01<00:33, 1.07it/s]\n 8%|▊ | 3/38 [00:02<00:32, 1.07it/s]\n 11%|█ | 4/38 [00:03<00:31, 1.07it/s]\n 13%|█▎ | 5/38 [00:04<00:30, 1.07it/s]\n 16%|█▌ | 6/38 [00:05<00:29, 1.07it/s]\n 18%|█▊ | 7/38 [00:06<00:28, 1.07it/s]\n 21%|██ | 8/38 [00:07<00:27, 1.07it/s]\n 24%|██▎ | 9/38 [00:08<00:27, 1.07it/s]\n 26%|██▋ | 10/38 [00:09<00:26, 1.07it/s]\n 29%|██▉ | 11/38 [00:10<00:25, 1.07it/s]\n 32%|███▏ | 12/38 [00:11<00:24, 1.07it/s]\n 34%|███▍ | 13/38 [00:12<00:23, 1.07it/s]\n 37%|███▋ | 14/38 [00:13<00:22, 1.07it/s]\n 39%|███▉ | 15/38 [00:13<00:21, 1.07it/s]\n 42%|████▏ | 16/38 [00:14<00:20, 1.07it/s]\n 45%|████▍ | 17/38 [00:15<00:19, 1.07it/s]\n 47%|████▋ | 18/38 [00:16<00:18, 1.07it/s]\n 50%|█████ | 19/38 [00:17<00:17, 1.07it/s]\n 53%|█████▎ | 20/38 [00:18<00:16, 1.07it/s]\n 55%|█████▌ | 21/38 [00:19<00:15, 1.07it/s]\n 58%|█████▊ | 22/38 [00:20<00:14, 1.07it/s]\n 61%|██████ | 23/38 [00:21<00:14, 1.07it/s]\n 63%|██████▎ | 24/38 [00:22<00:13, 1.07it/s]\n 66%|██████▌ | 25/38 [00:23<00:12, 1.07it/s]\n 68%|██████▊ | 26/38 [00:24<00:11, 1.07it/s]\n 71%|███████ | 27/38 [00:25<00:10, 1.07it/s]\n 74%|███████▎ | 28/38 [00:26<00:09, 1.07it/s]\n 76%|███████▋ | 29/38 [00:27<00:08, 1.07it/s]\n 79%|███████▉ | 30/38 [00:28<00:07, 1.07it/s]\n 82%|████████▏ | 31/38 [00:28<00:06, 1.07it/s]\n 84%|████████▍ | 32/38 [00:29<00:05, 1.07it/s]\n 87%|████████▋ | 33/38 [00:30<00:04, 1.07it/s]\n 89%|████████▉ | 34/38 [00:31<00:03, 1.07it/s]\n 92%|█████████▏| 35/38 [00:32<00:02, 1.06it/s]\n 95%|█████████▍| 36/38 [00:33<00:01, 1.07it/s]\n 97%|█████████▋| 37/38 [00:34<00:00, 1.07it/s]\n100%|██████████| 38/38 [00:35<00:00, 1.07it/s]\n100%|██████████| 38/38 [00:35<00:00, 1.07it/s]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:01, 1.23it/s]\n 67%|██████▋ | 2/3 [00:01<00:00, 1.23it/s]\n100%|██████████| 3/3 [00:02<00:00, 1.23it/s]\n100%|██████████| 3/3 [00:02<00:00, 1.23it/s]", "metrics": { "predict_time": 43.762994, "total_time": 43.693773 }, "output": [ "https://replicate.delivery/pbxt/7cbo298LPXKdMpe9htnJ5OV34jG9MO3e9tpLsdDsthVIN71RA/out-0.png", "https://replicate.delivery/pbxt/WBbhOjv3vu6NF1L1i8UNvTieiLRnM2eLs2LShBPH3tpJN71RA/out-1.png", "https://replicate.delivery/pbxt/8pJDuNEI2w4zK52AUBfpcVFetbzfIYTtEzXEypBTn2nVa2rjA/out-2.png", "https://replicate.delivery/pbxt/QDIbGJNlBWLHMdxv9YsooCXeYJoCLoZhYGCmfxKfSrAUa2rjA/out-3.png" ], "started_at": "2023-11-07T09:19:27.301814Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/xaztsqtbv2unf526zztmqljtjq", "cancel": "https://api.replicate.com/v1/predictions/xaztsqtbv2unf526zztmqljtjq/cancel" }, "version": "6cd71fdb0694e8b04c81882340082864b55b591b4d3b6cb3b949ca2b28592446" }
Generated inUsing seed: 3472 Prompt: animated picture of a single-family house in the style of <s0><s1>, clean, simple txt2img mode 0%| | 0/38 [00:00<?, ?it/s] 3%|▎ | 1/38 [00:00<00:34, 1.07it/s] 5%|▌ | 2/38 [00:01<00:33, 1.07it/s] 8%|▊ | 3/38 [00:02<00:32, 1.07it/s] 11%|█ | 4/38 [00:03<00:31, 1.07it/s] 13%|█▎ | 5/38 [00:04<00:30, 1.07it/s] 16%|█▌ | 6/38 [00:05<00:29, 1.07it/s] 18%|█▊ | 7/38 [00:06<00:28, 1.07it/s] 21%|██ | 8/38 [00:07<00:27, 1.07it/s] 24%|██▎ | 9/38 [00:08<00:27, 1.07it/s] 26%|██▋ | 10/38 [00:09<00:26, 1.07it/s] 29%|██▉ | 11/38 [00:10<00:25, 1.07it/s] 32%|███▏ | 12/38 [00:11<00:24, 1.07it/s] 34%|███▍ | 13/38 [00:12<00:23, 1.07it/s] 37%|███▋ | 14/38 [00:13<00:22, 1.07it/s] 39%|███▉ | 15/38 [00:13<00:21, 1.07it/s] 42%|████▏ | 16/38 [00:14<00:20, 1.07it/s] 45%|████▍ | 17/38 [00:15<00:19, 1.07it/s] 47%|████▋ | 18/38 [00:16<00:18, 1.07it/s] 50%|█████ | 19/38 [00:17<00:17, 1.07it/s] 53%|█████▎ | 20/38 [00:18<00:16, 1.07it/s] 55%|█████▌ | 21/38 [00:19<00:15, 1.07it/s] 58%|█████▊ | 22/38 [00:20<00:14, 1.07it/s] 61%|██████ | 23/38 [00:21<00:14, 1.07it/s] 63%|██████▎ | 24/38 [00:22<00:13, 1.07it/s] 66%|██████▌ | 25/38 [00:23<00:12, 1.07it/s] 68%|██████▊ | 26/38 [00:24<00:11, 1.07it/s] 71%|███████ | 27/38 [00:25<00:10, 1.07it/s] 74%|███████▎ | 28/38 [00:26<00:09, 1.07it/s] 76%|███████▋ | 29/38 [00:27<00:08, 1.07it/s] 79%|███████▉ | 30/38 [00:28<00:07, 1.07it/s] 82%|████████▏ | 31/38 [00:28<00:06, 1.07it/s] 84%|████████▍ | 32/38 [00:29<00:05, 1.07it/s] 87%|████████▋ | 33/38 [00:30<00:04, 1.07it/s] 89%|████████▉ | 34/38 [00:31<00:03, 1.07it/s] 92%|█████████▏| 35/38 [00:32<00:02, 1.06it/s] 95%|█████████▍| 36/38 [00:33<00:01, 1.07it/s] 97%|█████████▋| 37/38 [00:34<00:00, 1.07it/s] 100%|██████████| 38/38 [00:35<00:00, 1.07it/s] 100%|██████████| 38/38 [00:35<00:00, 1.07it/s] 0%| | 0/3 [00:00<?, ?it/s] 33%|███▎ | 1/3 [00:00<00:01, 1.23it/s] 67%|██████▋ | 2/3 [00:01<00:00, 1.23it/s] 100%|██████████| 3/3 [00:02<00:00, 1.23it/s] 100%|██████████| 3/3 [00:02<00:00, 1.23it/s]
Prediction
ghostofpokemon/sdxl-family-guy:6cd71fdb0694e8b04c81882340082864b55b591b4d3b6cb3b949ca2b28592446ID4uqxyttb3ybsqoyxiuo2lt3hkyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1280
- height
- 720
- prompt
- A picture of a house in the style of TOK, clean, simple
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.87
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- underexposed, ugly, broken
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1280, "height": 720, "prompt": "A picture of a house in the style of TOK, clean, simple", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.87, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "underexposed, ugly, broken", "prompt_strength": 0.8, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ghostofpokemon/sdxl-family-guy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ghostofpokemon/sdxl-family-guy:6cd71fdb0694e8b04c81882340082864b55b591b4d3b6cb3b949ca2b28592446", { input: { width: 1280, height: 720, prompt: "A picture of a house in the style of TOK, clean, simple", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.87, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "underexposed, ugly, broken", 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 replicate
Import the client:import replicate
Run ghostofpokemon/sdxl-family-guy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ghostofpokemon/sdxl-family-guy:6cd71fdb0694e8b04c81882340082864b55b591b4d3b6cb3b949ca2b28592446", input={ "width": 1280, "height": 720, "prompt": "A picture of a house in the style of TOK, clean, simple", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.87, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "underexposed, ugly, broken", "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 ghostofpokemon/sdxl-family-guy 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": "ghostofpokemon/sdxl-family-guy:6cd71fdb0694e8b04c81882340082864b55b591b4d3b6cb3b949ca2b28592446", "input": { "width": 1280, "height": 720, "prompt": "A picture of a house in the style of TOK, clean, simple", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.87, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "underexposed, ugly, broken", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-07T09:23:32.621482Z", "created_at": "2023-11-07T09:23:18.391746Z", "data_removed": false, "error": null, "id": "4uqxyttb3ybsqoyxiuo2lt3hky", "input": { "width": 1280, "height": 720, "prompt": "A picture of a house in the style of TOK, clean, simple", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.87, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "underexposed, ugly, broken", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 2874\nPrompt: A picture of a house in the style of <s0><s1>, clean, simple\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:11, 4.14it/s]\n 4%|▍ | 2/50 [00:00<00:11, 4.12it/s]\n 6%|▌ | 3/50 [00:00<00:11, 4.11it/s]\n 8%|▊ | 4/50 [00:00<00:11, 4.11it/s]\n 10%|█ | 5/50 [00:01<00:10, 4.11it/s]\n 12%|█▏ | 6/50 [00:01<00:10, 4.11it/s]\n 14%|█▍ | 7/50 [00:01<00:10, 4.11it/s]\n 16%|█▌ | 8/50 [00:01<00:10, 4.11it/s]\n 18%|█▊ | 9/50 [00:02<00:09, 4.11it/s]\n 20%|██ | 10/50 [00:02<00:09, 4.10it/s]\n 22%|██▏ | 11/50 [00:02<00:09, 4.10it/s]\n 24%|██▍ | 12/50 [00:02<00:09, 4.10it/s]\n 26%|██▌ | 13/50 [00:03<00:09, 4.10it/s]\n 28%|██▊ | 14/50 [00:03<00:08, 4.10it/s]\n 30%|███ | 15/50 [00:03<00:08, 4.11it/s]\n 32%|███▏ | 16/50 [00:03<00:08, 4.11it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 4.12it/s]\n 36%|███▌ | 18/50 [00:04<00:07, 4.12it/s]\n 38%|███▊ | 19/50 [00:04<00:07, 4.12it/s]\n 40%|████ | 20/50 [00:04<00:07, 4.12it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 4.12it/s]\n 44%|████▍ | 22/50 [00:05<00:06, 4.12it/s]\n 46%|████▌ | 23/50 [00:05<00:06, 4.12it/s]\n 48%|████▊ | 24/50 [00:05<00:06, 4.12it/s]\n 50%|█████ | 25/50 [00:06<00:06, 4.12it/s]\n 52%|█████▏ | 26/50 [00:06<00:05, 4.12it/s]\n 54%|█████▍ | 27/50 [00:06<00:05, 4.12it/s]\n 56%|█████▌ | 28/50 [00:06<00:05, 4.12it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 4.12it/s]\n 60%|██████ | 30/50 [00:07<00:04, 4.12it/s]\n 62%|██████▏ | 31/50 [00:07<00:04, 4.12it/s]\n 64%|██████▍ | 32/50 [00:07<00:04, 4.12it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 4.12it/s]\n 68%|██████▊ | 34/50 [00:08<00:03, 4.12it/s]\n 70%|███████ | 35/50 [00:08<00:03, 4.12it/s]\n 72%|███████▏ | 36/50 [00:08<00:03, 4.12it/s]\n 74%|███████▍ | 37/50 [00:08<00:03, 4.12it/s]\n 76%|███████▌ | 38/50 [00:09<00:02, 4.12it/s]\n 78%|███████▊ | 39/50 [00:09<00:02, 4.10it/s]\n 80%|████████ | 40/50 [00:09<00:02, 4.08it/s]\n 82%|████████▏ | 41/50 [00:09<00:02, 4.09it/s]\n 84%|████████▍ | 42/50 [00:10<00:01, 4.10it/s]\n 86%|████████▌ | 43/50 [00:10<00:01, 4.10it/s]\n 88%|████████▊ | 44/50 [00:10<00:01, 4.10it/s]\n 90%|█████████ | 45/50 [00:10<00:01, 4.11it/s]\n 92%|█████████▏| 46/50 [00:11<00:00, 4.11it/s]\n 94%|█████████▍| 47/50 [00:11<00:00, 4.10it/s]\n 96%|█████████▌| 48/50 [00:11<00:00, 4.11it/s]\n 98%|█████████▊| 49/50 [00:11<00:00, 4.11it/s]\n100%|██████████| 50/50 [00:12<00:00, 4.11it/s]\n100%|██████████| 50/50 [00:12<00:00, 4.11it/s]", "metrics": { "predict_time": 14.261328, "total_time": 14.229736 }, "output": [ "https://replicate.delivery/pbxt/EsCIkXyZfb1rbqcCqgLkw5xIfYQ0nv62UMomixFDa9CTQ71RA/out-0.png" ], "started_at": "2023-11-07T09:23:18.360154Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/4uqxyttb3ybsqoyxiuo2lt3hky", "cancel": "https://api.replicate.com/v1/predictions/4uqxyttb3ybsqoyxiuo2lt3hky/cancel" }, "version": "6cd71fdb0694e8b04c81882340082864b55b591b4d3b6cb3b949ca2b28592446" }
Generated inUsing seed: 2874 Prompt: A picture of a house in the style of <s0><s1>, clean, simple txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:11, 4.14it/s] 4%|▍ | 2/50 [00:00<00:11, 4.12it/s] 6%|▌ | 3/50 [00:00<00:11, 4.11it/s] 8%|▊ | 4/50 [00:00<00:11, 4.11it/s] 10%|█ | 5/50 [00:01<00:10, 4.11it/s] 12%|█▏ | 6/50 [00:01<00:10, 4.11it/s] 14%|█▍ | 7/50 [00:01<00:10, 4.11it/s] 16%|█▌ | 8/50 [00:01<00:10, 4.11it/s] 18%|█▊ | 9/50 [00:02<00:09, 4.11it/s] 20%|██ | 10/50 [00:02<00:09, 4.10it/s] 22%|██▏ | 11/50 [00:02<00:09, 4.10it/s] 24%|██▍ | 12/50 [00:02<00:09, 4.10it/s] 26%|██▌ | 13/50 [00:03<00:09, 4.10it/s] 28%|██▊ | 14/50 [00:03<00:08, 4.10it/s] 30%|███ | 15/50 [00:03<00:08, 4.11it/s] 32%|███▏ | 16/50 [00:03<00:08, 4.11it/s] 34%|███▍ | 17/50 [00:04<00:08, 4.12it/s] 36%|███▌ | 18/50 [00:04<00:07, 4.12it/s] 38%|███▊ | 19/50 [00:04<00:07, 4.12it/s] 40%|████ | 20/50 [00:04<00:07, 4.12it/s] 42%|████▏ | 21/50 [00:05<00:07, 4.12it/s] 44%|████▍ | 22/50 [00:05<00:06, 4.12it/s] 46%|████▌ | 23/50 [00:05<00:06, 4.12it/s] 48%|████▊ | 24/50 [00:05<00:06, 4.12it/s] 50%|█████ | 25/50 [00:06<00:06, 4.12it/s] 52%|█████▏ | 26/50 [00:06<00:05, 4.12it/s] 54%|█████▍ | 27/50 [00:06<00:05, 4.12it/s] 56%|█████▌ | 28/50 [00:06<00:05, 4.12it/s] 58%|█████▊ | 29/50 [00:07<00:05, 4.12it/s] 60%|██████ | 30/50 [00:07<00:04, 4.12it/s] 62%|██████▏ | 31/50 [00:07<00:04, 4.12it/s] 64%|██████▍ | 32/50 [00:07<00:04, 4.12it/s] 66%|██████▌ | 33/50 [00:08<00:04, 4.12it/s] 68%|██████▊ | 34/50 [00:08<00:03, 4.12it/s] 70%|███████ | 35/50 [00:08<00:03, 4.12it/s] 72%|███████▏ | 36/50 [00:08<00:03, 4.12it/s] 74%|███████▍ | 37/50 [00:08<00:03, 4.12it/s] 76%|███████▌ | 38/50 [00:09<00:02, 4.12it/s] 78%|███████▊ | 39/50 [00:09<00:02, 4.10it/s] 80%|████████ | 40/50 [00:09<00:02, 4.08it/s] 82%|████████▏ | 41/50 [00:09<00:02, 4.09it/s] 84%|████████▍ | 42/50 [00:10<00:01, 4.10it/s] 86%|████████▌ | 43/50 [00:10<00:01, 4.10it/s] 88%|████████▊ | 44/50 [00:10<00:01, 4.10it/s] 90%|█████████ | 45/50 [00:10<00:01, 4.11it/s] 92%|█████████▏| 46/50 [00:11<00:00, 4.11it/s] 94%|█████████▍| 47/50 [00:11<00:00, 4.10it/s] 96%|█████████▌| 48/50 [00:11<00:00, 4.11it/s] 98%|█████████▊| 49/50 [00:11<00:00, 4.11it/s] 100%|██████████| 50/50 [00:12<00:00, 4.11it/s] 100%|██████████| 50/50 [00:12<00:00, 4.11it/s]
Prediction
ghostofpokemon/sdxl-family-guy:627e586922efd4d502e181ac0491ed30fe96c20a046c561f03865cc6849644f9IDf5cc6i3bwv4yw7qcpish56g2uyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 576
- prompt
- A picture of a house in the style of Family Guy, clean, simple
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.87
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- underexposed, ugly, broken
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 576, "prompt": "A picture of a house in the style of Family Guy, clean, simple", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.87, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "underexposed, ugly, broken", "prompt_strength": 0.8, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ghostofpokemon/sdxl-family-guy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ghostofpokemon/sdxl-family-guy:627e586922efd4d502e181ac0491ed30fe96c20a046c561f03865cc6849644f9", { input: { width: 1024, height: 576, prompt: "A picture of a house in the style of Family Guy, clean, simple", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.87, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "underexposed, ugly, broken", 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 replicate
Import the client:import replicate
Run ghostofpokemon/sdxl-family-guy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ghostofpokemon/sdxl-family-guy:627e586922efd4d502e181ac0491ed30fe96c20a046c561f03865cc6849644f9", input={ "width": 1024, "height": 576, "prompt": "A picture of a house in the style of Family Guy, clean, simple", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.87, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "underexposed, ugly, broken", "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 ghostofpokemon/sdxl-family-guy 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": "ghostofpokemon/sdxl-family-guy:627e586922efd4d502e181ac0491ed30fe96c20a046c561f03865cc6849644f9", "input": { "width": 1024, "height": 576, "prompt": "A picture of a house in the style of Family Guy, clean, simple", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.87, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "underexposed, ugly, broken", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-12T20:03:28.166621Z", "created_at": "2023-11-12T20:02:20.697598Z", "data_removed": false, "error": null, "id": "f5cc6i3bwv4yw7qcpish56g2uy", "input": { "width": 1024, "height": 576, "prompt": "A picture of a house in the style of Family Guy, clean, simple", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.87, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "underexposed, ugly, broken", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 26272\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: A picture of a house in the style of <s0><s1>, clean, simple\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:07, 6.15it/s]\n 4%|▍ | 2/50 [00:00<00:07, 6.12it/s]\n 6%|▌ | 3/50 [00:00<00:07, 6.10it/s]\n 8%|▊ | 4/50 [00:00<00:07, 6.09it/s]\n 10%|█ | 5/50 [00:00<00:07, 6.09it/s]\n 12%|█▏ | 6/50 [00:00<00:07, 6.10it/s]\n 14%|█▍ | 7/50 [00:01<00:07, 6.10it/s]\n 16%|█▌ | 8/50 [00:01<00:06, 6.09it/s]\n 18%|█▊ | 9/50 [00:01<00:06, 6.09it/s]\n 20%|██ | 10/50 [00:01<00:06, 6.09it/s]\n 22%|██▏ | 11/50 [00:01<00:06, 6.11it/s]\n 24%|██▍ | 12/50 [00:01<00:06, 6.12it/s]\n 26%|██▌ | 13/50 [00:02<00:06, 6.12it/s]\n 28%|██▊ | 14/50 [00:02<00:05, 6.12it/s]\n 30%|███ | 15/50 [00:02<00:05, 6.12it/s]\n 32%|███▏ | 16/50 [00:02<00:05, 6.12it/s]\n 34%|███▍ | 17/50 [00:02<00:05, 6.12it/s]\n 36%|███▌ | 18/50 [00:02<00:05, 6.12it/s]\n 38%|███▊ | 19/50 [00:03<00:05, 6.12it/s]\n 40%|████ | 20/50 [00:03<00:04, 6.12it/s]\n 42%|████▏ | 21/50 [00:03<00:04, 6.12it/s]\n 44%|████▍ | 22/50 [00:03<00:04, 6.12it/s]\n 46%|████▌ | 23/50 [00:03<00:04, 6.12it/s]\n 48%|████▊ | 24/50 [00:03<00:04, 6.12it/s]\n 50%|█████ | 25/50 [00:04<00:04, 6.12it/s]\n 52%|█████▏ | 26/50 [00:04<00:03, 6.12it/s]\n 54%|█████▍ | 27/50 [00:04<00:03, 6.12it/s]\n 56%|█████▌ | 28/50 [00:04<00:03, 6.12it/s]\n 58%|█████▊ | 29/50 [00:04<00:03, 6.12it/s]\n 60%|██████ | 30/50 [00:04<00:03, 6.12it/s]\n 62%|██████▏ | 31/50 [00:05<00:03, 6.12it/s]\n 64%|██████▍ | 32/50 [00:05<00:02, 6.12it/s]\n 66%|██████▌ | 33/50 [00:05<00:02, 6.12it/s]\n 68%|██████▊ | 34/50 [00:05<00:02, 6.12it/s]\n 70%|███████ | 35/50 [00:05<00:02, 6.12it/s]\n 72%|███████▏ | 36/50 [00:05<00:02, 6.12it/s]\n 74%|███████▍ | 37/50 [00:06<00:02, 6.12it/s]\n 76%|███████▌ | 38/50 [00:06<00:01, 6.11it/s]\n 78%|███████▊ | 39/50 [00:06<00:01, 6.11it/s]\n 80%|████████ | 40/50 [00:06<00:01, 6.10it/s]\n 82%|████████▏ | 41/50 [00:06<00:01, 6.10it/s]\n 84%|████████▍ | 42/50 [00:06<00:01, 6.11it/s]\n 86%|████████▌ | 43/50 [00:07<00:01, 6.11it/s]\n 88%|████████▊ | 44/50 [00:07<00:00, 6.11it/s]\n 90%|█████████ | 45/50 [00:07<00:00, 6.11it/s]\n 92%|█████████▏| 46/50 [00:07<00:00, 6.11it/s]\n 94%|█████████▍| 47/50 [00:07<00:00, 6.11it/s]\n 96%|█████████▌| 48/50 [00:07<00:00, 6.11it/s]\n 98%|█████████▊| 49/50 [00:08<00:00, 6.11it/s]\n100%|██████████| 50/50 [00:08<00:00, 6.11it/s]\n100%|██████████| 50/50 [00:08<00:00, 6.11it/s]", "metrics": { "predict_time": 10.447804, "total_time": 67.469023 }, "output": [ "https://replicate.delivery/pbxt/fsqYRVRQcZzHPyeAr9sUxwhq9RJRFWeT3qGubi5vdLifY4eOC/out-0.png" ], "started_at": "2023-11-12T20:03:17.718817Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/f5cc6i3bwv4yw7qcpish56g2uy", "cancel": "https://api.replicate.com/v1/predictions/f5cc6i3bwv4yw7qcpish56g2uy/cancel" }, "version": "627e586922efd4d502e181ac0491ed30fe96c20a046c561f03865cc6849644f9" }
Generated inUsing seed: 26272 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: A picture of a house in the style of <s0><s1>, clean, simple txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:07, 6.15it/s] 4%|▍ | 2/50 [00:00<00:07, 6.12it/s] 6%|▌ | 3/50 [00:00<00:07, 6.10it/s] 8%|▊ | 4/50 [00:00<00:07, 6.09it/s] 10%|█ | 5/50 [00:00<00:07, 6.09it/s] 12%|█▏ | 6/50 [00:00<00:07, 6.10it/s] 14%|█▍ | 7/50 [00:01<00:07, 6.10it/s] 16%|█▌ | 8/50 [00:01<00:06, 6.09it/s] 18%|█▊ | 9/50 [00:01<00:06, 6.09it/s] 20%|██ | 10/50 [00:01<00:06, 6.09it/s] 22%|██▏ | 11/50 [00:01<00:06, 6.11it/s] 24%|██▍ | 12/50 [00:01<00:06, 6.12it/s] 26%|██▌ | 13/50 [00:02<00:06, 6.12it/s] 28%|██▊ | 14/50 [00:02<00:05, 6.12it/s] 30%|███ | 15/50 [00:02<00:05, 6.12it/s] 32%|███▏ | 16/50 [00:02<00:05, 6.12it/s] 34%|███▍ | 17/50 [00:02<00:05, 6.12it/s] 36%|███▌ | 18/50 [00:02<00:05, 6.12it/s] 38%|███▊ | 19/50 [00:03<00:05, 6.12it/s] 40%|████ | 20/50 [00:03<00:04, 6.12it/s] 42%|████▏ | 21/50 [00:03<00:04, 6.12it/s] 44%|████▍ | 22/50 [00:03<00:04, 6.12it/s] 46%|████▌ | 23/50 [00:03<00:04, 6.12it/s] 48%|████▊ | 24/50 [00:03<00:04, 6.12it/s] 50%|█████ | 25/50 [00:04<00:04, 6.12it/s] 52%|█████▏ | 26/50 [00:04<00:03, 6.12it/s] 54%|█████▍ | 27/50 [00:04<00:03, 6.12it/s] 56%|█████▌ | 28/50 [00:04<00:03, 6.12it/s] 58%|█████▊ | 29/50 [00:04<00:03, 6.12it/s] 60%|██████ | 30/50 [00:04<00:03, 6.12it/s] 62%|██████▏ | 31/50 [00:05<00:03, 6.12it/s] 64%|██████▍ | 32/50 [00:05<00:02, 6.12it/s] 66%|██████▌ | 33/50 [00:05<00:02, 6.12it/s] 68%|██████▊ | 34/50 [00:05<00:02, 6.12it/s] 70%|███████ | 35/50 [00:05<00:02, 6.12it/s] 72%|███████▏ | 36/50 [00:05<00:02, 6.12it/s] 74%|███████▍ | 37/50 [00:06<00:02, 6.12it/s] 76%|███████▌ | 38/50 [00:06<00:01, 6.11it/s] 78%|███████▊ | 39/50 [00:06<00:01, 6.11it/s] 80%|████████ | 40/50 [00:06<00:01, 6.10it/s] 82%|████████▏ | 41/50 [00:06<00:01, 6.10it/s] 84%|████████▍ | 42/50 [00:06<00:01, 6.11it/s] 86%|████████▌ | 43/50 [00:07<00:01, 6.11it/s] 88%|████████▊ | 44/50 [00:07<00:00, 6.11it/s] 90%|█████████ | 45/50 [00:07<00:00, 6.11it/s] 92%|█████████▏| 46/50 [00:07<00:00, 6.11it/s] 94%|█████████▍| 47/50 [00:07<00:00, 6.11it/s] 96%|█████████▌| 48/50 [00:07<00:00, 6.11it/s] 98%|█████████▊| 49/50 [00:08<00:00, 6.11it/s] 100%|██████████| 50/50 [00:08<00:00, 6.11it/s] 100%|██████████| 50/50 [00:08<00:00, 6.11it/s]
Prediction
ghostofpokemon/sdxl-family-guy:4339b367ceed5d9b1b96e29245e3ec367745422b8d3cc9a6b1e83b66f68943d1IDd73jfnlbuhwro2hutjqpy5cmsiStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 13888
- width
- 1024
- height
- 576
- prompt
- A picture of a house in the style of Family Guy, clean, simple
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.87
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.95
- negative_prompt
- underexposed, ugly, broken
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "seed": 13888, "width": 1024, "height": 576, "prompt": "A picture of a house in the style of Family Guy, clean, simple", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.87, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.95, "negative_prompt": "underexposed, ugly, broken", "prompt_strength": 0.8, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ghostofpokemon/sdxl-family-guy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ghostofpokemon/sdxl-family-guy:4339b367ceed5d9b1b96e29245e3ec367745422b8d3cc9a6b1e83b66f68943d1", { input: { seed: 13888, width: 1024, height: 576, prompt: "A picture of a house in the style of Family Guy, clean, simple", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.87, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.95, negative_prompt: "underexposed, ugly, broken", 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 replicate
Import the client:import replicate
Run ghostofpokemon/sdxl-family-guy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ghostofpokemon/sdxl-family-guy:4339b367ceed5d9b1b96e29245e3ec367745422b8d3cc9a6b1e83b66f68943d1", input={ "seed": 13888, "width": 1024, "height": 576, "prompt": "A picture of a house in the style of Family Guy, clean, simple", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.87, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.95, "negative_prompt": "underexposed, ugly, broken", "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 ghostofpokemon/sdxl-family-guy 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": "ghostofpokemon/sdxl-family-guy:4339b367ceed5d9b1b96e29245e3ec367745422b8d3cc9a6b1e83b66f68943d1", "input": { "seed": 13888, "width": 1024, "height": 576, "prompt": "A picture of a house in the style of Family Guy, clean, simple", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.87, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.95, "negative_prompt": "underexposed, ugly, broken", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-19T03:39:00.122309Z", "created_at": "2023-11-19T03:38:42.674024Z", "data_removed": false, "error": null, "id": "d73jfnlbuhwro2hutjqpy5cmsi", "input": { "seed": 13888, "width": 1024, "height": 576, "prompt": "A picture of a house in the style of Family Guy, clean, simple", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.87, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.95, "negative_prompt": "underexposed, ugly, broken", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 13888\nEnsuring enough disk space...\nFree disk space: 2030540369920\nDownloading weights: https://replicate.delivery/pbxt/GID77w3Tdib1PtnqMP3FvBLmk1YNbw1hip2jfZerPRWPMy5RA/trained_model.tar\nb'Downloaded 186 MB bytes in 0.192s (968 MB/s)\\nExtracted 186 MB in 0.067s (2.8 GB/s)\\n'\nDownloaded weights in 0.3769724369049072 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: A picture of a house in the style of <s0><s1>, clean, simple\ntxt2img mode\n 0%| | 0/47 [00:00<?, ?it/s]\n 2%|▏ | 1/47 [00:00<00:08, 5.23it/s]\n 4%|▍ | 2/47 [00:00<00:08, 5.58it/s]\n 6%|▋ | 3/47 [00:00<00:07, 5.71it/s]\n 9%|▊ | 4/47 [00:00<00:07, 5.77it/s]\n 11%|█ | 5/47 [00:00<00:07, 5.80it/s]\n 13%|█▎ | 6/47 [00:01<00:07, 5.82it/s]\n 15%|█▍ | 7/47 [00:01<00:06, 5.83it/s]\n 17%|█▋ | 8/47 [00:01<00:06, 5.84it/s]\n 19%|█▉ | 9/47 [00:01<00:06, 5.85it/s]\n 21%|██▏ | 10/47 [00:01<00:06, 5.85it/s]\n 23%|██▎ | 11/47 [00:01<00:06, 5.85it/s]\n 26%|██▌ | 12/47 [00:02<00:05, 5.85it/s]\n 28%|██▊ | 13/47 [00:02<00:05, 5.86it/s]\n 30%|██▉ | 14/47 [00:02<00:05, 5.86it/s]\n 32%|███▏ | 15/47 [00:02<00:05, 5.85it/s]\n 34%|███▍ | 16/47 [00:02<00:05, 5.85it/s]\n 36%|███▌ | 17/47 [00:02<00:05, 5.85it/s]\n 38%|███▊ | 18/47 [00:03<00:04, 5.85it/s]\n 40%|████ | 19/47 [00:03<00:04, 5.85it/s]\n 43%|████▎ | 20/47 [00:03<00:04, 5.85it/s]\n 45%|████▍ | 21/47 [00:03<00:04, 5.85it/s]\n 47%|████▋ | 22/47 [00:03<00:04, 5.85it/s]\n 49%|████▉ | 23/47 [00:03<00:04, 5.84it/s]\n 51%|█████ | 24/47 [00:04<00:03, 5.84it/s]\n 53%|█████▎ | 25/47 [00:04<00:03, 5.84it/s]\n 55%|█████▌ | 26/47 [00:04<00:03, 5.84it/s]\n 57%|█████▋ | 27/47 [00:04<00:03, 5.83it/s]\n 60%|█████▉ | 28/47 [00:04<00:03, 5.83it/s]\n 62%|██████▏ | 29/47 [00:04<00:03, 5.82it/s]\n 64%|██████▍ | 30/47 [00:05<00:02, 5.82it/s]\n 66%|██████▌ | 31/47 [00:05<00:02, 5.82it/s]\n 68%|██████▊ | 32/47 [00:05<00:02, 5.82it/s]\n 70%|███████ | 33/47 [00:05<00:02, 5.82it/s]\n 72%|███████▏ | 34/47 [00:05<00:02, 5.82it/s]\n 74%|███████▍ | 35/47 [00:06<00:02, 5.82it/s]\n 77%|███████▋ | 36/47 [00:06<00:01, 5.82it/s]\n 79%|███████▊ | 37/47 [00:06<00:01, 5.82it/s]\n 81%|████████ | 38/47 [00:06<00:01, 5.81it/s]\n 83%|████████▎ | 39/47 [00:06<00:01, 5.81it/s]\n 85%|████████▌ | 40/47 [00:06<00:01, 5.81it/s]\n 87%|████████▋ | 41/47 [00:07<00:01, 5.81it/s]\n 89%|████████▉ | 42/47 [00:07<00:00, 5.81it/s]\n 91%|█████████▏| 43/47 [00:07<00:00, 5.81it/s]\n 94%|█████████▎| 44/47 [00:07<00:00, 5.81it/s]\n 96%|█████████▌| 45/47 [00:07<00:00, 5.81it/s]\n 98%|█████████▊| 46/47 [00:07<00:00, 5.81it/s]\n100%|██████████| 47/47 [00:08<00:00, 5.81it/s]\n100%|██████████| 47/47 [00:08<00:00, 5.82it/s]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:00, 6.71it/s]\n 67%|██████▋ | 2/3 [00:00<00:00, 7.06it/s]\n100%|██████████| 3/3 [00:00<00:00, 7.17it/s]\n100%|██████████| 3/3 [00:00<00:00, 7.10it/s]", "metrics": { "predict_time": 11.238864, "total_time": 17.448285 }, "output": [ "https://replicate.delivery/pbxt/ewrWUvOa0oXWR6dOXrqFN2hcxXA1Al0rztUOJTmvsClpq58IA/out-0.png" ], "started_at": "2023-11-19T03:38:48.883445Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/d73jfnlbuhwro2hutjqpy5cmsi", "cancel": "https://api.replicate.com/v1/predictions/d73jfnlbuhwro2hutjqpy5cmsi/cancel" }, "version": "4339b367ceed5d9b1b96e29245e3ec367745422b8d3cc9a6b1e83b66f68943d1" }
Generated inUsing seed: 13888 Ensuring enough disk space... Free disk space: 2030540369920 Downloading weights: https://replicate.delivery/pbxt/GID77w3Tdib1PtnqMP3FvBLmk1YNbw1hip2jfZerPRWPMy5RA/trained_model.tar b'Downloaded 186 MB bytes in 0.192s (968 MB/s)\nExtracted 186 MB in 0.067s (2.8 GB/s)\n' Downloaded weights in 0.3769724369049072 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: A picture of a house in the style of <s0><s1>, clean, simple txt2img mode 0%| | 0/47 [00:00<?, ?it/s] 2%|▏ | 1/47 [00:00<00:08, 5.23it/s] 4%|▍ | 2/47 [00:00<00:08, 5.58it/s] 6%|▋ | 3/47 [00:00<00:07, 5.71it/s] 9%|▊ | 4/47 [00:00<00:07, 5.77it/s] 11%|█ | 5/47 [00:00<00:07, 5.80it/s] 13%|█▎ | 6/47 [00:01<00:07, 5.82it/s] 15%|█▍ | 7/47 [00:01<00:06, 5.83it/s] 17%|█▋ | 8/47 [00:01<00:06, 5.84it/s] 19%|█▉ | 9/47 [00:01<00:06, 5.85it/s] 21%|██▏ | 10/47 [00:01<00:06, 5.85it/s] 23%|██▎ | 11/47 [00:01<00:06, 5.85it/s] 26%|██▌ | 12/47 [00:02<00:05, 5.85it/s] 28%|██▊ | 13/47 [00:02<00:05, 5.86it/s] 30%|██▉ | 14/47 [00:02<00:05, 5.86it/s] 32%|███▏ | 15/47 [00:02<00:05, 5.85it/s] 34%|███▍ | 16/47 [00:02<00:05, 5.85it/s] 36%|███▌ | 17/47 [00:02<00:05, 5.85it/s] 38%|███▊ | 18/47 [00:03<00:04, 5.85it/s] 40%|████ | 19/47 [00:03<00:04, 5.85it/s] 43%|████▎ | 20/47 [00:03<00:04, 5.85it/s] 45%|████▍ | 21/47 [00:03<00:04, 5.85it/s] 47%|████▋ | 22/47 [00:03<00:04, 5.85it/s] 49%|████▉ | 23/47 [00:03<00:04, 5.84it/s] 51%|█████ | 24/47 [00:04<00:03, 5.84it/s] 53%|█████▎ | 25/47 [00:04<00:03, 5.84it/s] 55%|█████▌ | 26/47 [00:04<00:03, 5.84it/s] 57%|█████▋ | 27/47 [00:04<00:03, 5.83it/s] 60%|█████▉ | 28/47 [00:04<00:03, 5.83it/s] 62%|██████▏ | 29/47 [00:04<00:03, 5.82it/s] 64%|██████▍ | 30/47 [00:05<00:02, 5.82it/s] 66%|██████▌ | 31/47 [00:05<00:02, 5.82it/s] 68%|██████▊ | 32/47 [00:05<00:02, 5.82it/s] 70%|███████ | 33/47 [00:05<00:02, 5.82it/s] 72%|███████▏ | 34/47 [00:05<00:02, 5.82it/s] 74%|███████▍ | 35/47 [00:06<00:02, 5.82it/s] 77%|███████▋ | 36/47 [00:06<00:01, 5.82it/s] 79%|███████▊ | 37/47 [00:06<00:01, 5.82it/s] 81%|████████ | 38/47 [00:06<00:01, 5.81it/s] 83%|████████▎ | 39/47 [00:06<00:01, 5.81it/s] 85%|████████▌ | 40/47 [00:06<00:01, 5.81it/s] 87%|████████▋ | 41/47 [00:07<00:01, 5.81it/s] 89%|████████▉ | 42/47 [00:07<00:00, 5.81it/s] 91%|█████████▏| 43/47 [00:07<00:00, 5.81it/s] 94%|█████████▎| 44/47 [00:07<00:00, 5.81it/s] 96%|█████████▌| 45/47 [00:07<00:00, 5.81it/s] 98%|█████████▊| 46/47 [00:07<00:00, 5.81it/s] 100%|██████████| 47/47 [00:08<00:00, 5.81it/s] 100%|██████████| 47/47 [00:08<00:00, 5.82it/s] 0%| | 0/3 [00:00<?, ?it/s] 33%|███▎ | 1/3 [00:00<00:00, 6.71it/s] 67%|██████▋ | 2/3 [00:00<00:00, 7.06it/s] 100%|██████████| 3/3 [00:00<00:00, 7.17it/s] 100%|██████████| 3/3 [00:00<00:00, 7.10it/s]
Prediction
ghostofpokemon/sdxl-family-guy:4339b367ceed5d9b1b96e29245e3ec367745422b8d3cc9a6b1e83b66f68943d1IDecahymlb6qqbec34lkiwmjukgqStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 13888
- width
- 1024
- height
- 576
- prompt
- cat in a forest clearing surrounded by trees in the style of Family Guy, clean, simple
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.79
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- underexposed, ugly, broken
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "seed": 13888, "width": 1024, "height": 576, "prompt": "cat in a forest clearing surrounded by trees in the style of Family Guy, clean, simple", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.79, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "underexposed, ugly, broken", "prompt_strength": 0.8, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run ghostofpokemon/sdxl-family-guy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ghostofpokemon/sdxl-family-guy:4339b367ceed5d9b1b96e29245e3ec367745422b8d3cc9a6b1e83b66f68943d1", { input: { seed: 13888, width: 1024, height: 576, prompt: "cat in a forest clearing surrounded by trees in the style of Family Guy, clean, simple", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.79, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "underexposed, ugly, broken", 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 replicate
Import the client:import replicate
Run ghostofpokemon/sdxl-family-guy using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ghostofpokemon/sdxl-family-guy:4339b367ceed5d9b1b96e29245e3ec367745422b8d3cc9a6b1e83b66f68943d1", input={ "seed": 13888, "width": 1024, "height": 576, "prompt": "cat in a forest clearing surrounded by trees in the style of Family Guy, clean, simple", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.79, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "underexposed, ugly, broken", "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 ghostofpokemon/sdxl-family-guy 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": "ghostofpokemon/sdxl-family-guy:4339b367ceed5d9b1b96e29245e3ec367745422b8d3cc9a6b1e83b66f68943d1", "input": { "seed": 13888, "width": 1024, "height": 576, "prompt": "cat in a forest clearing surrounded by trees in the style of Family Guy, clean, simple", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.79, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "underexposed, ugly, broken", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-19T03:38:05.231274Z", "created_at": "2023-11-19T03:36:15.816856Z", "data_removed": false, "error": null, "id": "ecahymlb6qqbec34lkiwmjukgq", "input": { "seed": 13888, "width": 1024, "height": 576, "prompt": "cat in a forest clearing surrounded by trees in the style of Family Guy, clean, simple", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.79, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "underexposed, ugly, broken", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 13888\nEnsuring enough disk space...\nFree disk space: 1862720487424\nDownloading weights: https://replicate.delivery/pbxt/GID77w3Tdib1PtnqMP3FvBLmk1YNbw1hip2jfZerPRWPMy5RA/trained_model.tar\nb'Downloaded 186 MB bytes in 0.261s (712 MB/s)\\nExtracted 186 MB in 0.050s (3.7 GB/s)\\n'\nDownloaded weights in 0.3919353485107422 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: cat in a forest clearing surrounded by trees in the style of <s0><s1>, clean, simple\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:07, 6.20it/s]\n 4%|▍ | 2/50 [00:00<00:07, 6.19it/s]\n 6%|▌ | 3/50 [00:00<00:07, 6.18it/s]\n 8%|▊ | 4/50 [00:00<00:07, 6.17it/s]\n 10%|█ | 5/50 [00:00<00:07, 6.17it/s]\n 12%|█▏ | 6/50 [00:00<00:07, 6.17it/s]\n 14%|█▍ | 7/50 [00:01<00:06, 6.17it/s]\n 16%|█▌ | 8/50 [00:01<00:06, 6.16it/s]\n 18%|█▊ | 9/50 [00:01<00:06, 6.16it/s]\n 20%|██ | 10/50 [00:01<00:06, 6.16it/s]\n 22%|██▏ | 11/50 [00:01<00:06, 6.16it/s]\n 24%|██▍ | 12/50 [00:01<00:06, 6.15it/s]\n 26%|██▌ | 13/50 [00:02<00:06, 6.15it/s]\n 28%|██▊ | 14/50 [00:02<00:05, 6.15it/s]\n 30%|███ | 15/50 [00:02<00:05, 6.15it/s]\n 32%|███▏ | 16/50 [00:02<00:05, 6.14it/s]\n 34%|███▍ | 17/50 [00:02<00:05, 6.14it/s]\n 36%|███▌ | 18/50 [00:02<00:05, 6.14it/s]\n 38%|███▊ | 19/50 [00:03<00:05, 6.15it/s]\n 40%|████ | 20/50 [00:03<00:04, 6.15it/s]\n 42%|████▏ | 21/50 [00:03<00:04, 6.15it/s]\n 44%|████▍ | 22/50 [00:03<00:04, 6.14it/s]\n 46%|████▌ | 23/50 [00:03<00:04, 6.14it/s]\n 48%|████▊ | 24/50 [00:03<00:04, 6.14it/s]\n 50%|█████ | 25/50 [00:04<00:04, 6.15it/s]\n 52%|█████▏ | 26/50 [00:04<00:03, 6.15it/s]\n 54%|█████▍ | 27/50 [00:04<00:03, 6.15it/s]\n 56%|█████▌ | 28/50 [00:04<00:03, 6.15it/s]\n 58%|█████▊ | 29/50 [00:04<00:03, 6.15it/s]\n 60%|██████ | 30/50 [00:04<00:03, 6.14it/s]\n 62%|██████▏ | 31/50 [00:05<00:03, 6.13it/s]\n 64%|██████▍ | 32/50 [00:05<00:02, 6.14it/s]\n 66%|██████▌ | 33/50 [00:05<00:02, 6.14it/s]\n 68%|██████▊ | 34/50 [00:05<00:02, 6.14it/s]\n 70%|███████ | 35/50 [00:05<00:02, 6.14it/s]\n 72%|███████▏ | 36/50 [00:05<00:02, 6.14it/s]\n 74%|███████▍ | 37/50 [00:06<00:02, 6.13it/s]\n 76%|███████▌ | 38/50 [00:06<00:01, 6.13it/s]\n 78%|███████▊ | 39/50 [00:06<00:01, 6.14it/s]\n 80%|████████ | 40/50 [00:06<00:01, 6.15it/s]\n 82%|████████▏ | 41/50 [00:06<00:01, 6.16it/s]\n 84%|████████▍ | 42/50 [00:06<00:01, 6.17it/s]\n 86%|████████▌ | 43/50 [00:06<00:01, 6.17it/s]\n 88%|████████▊ | 44/50 [00:07<00:00, 6.17it/s]\n 90%|█████████ | 45/50 [00:07<00:00, 6.17it/s]\n 92%|█████████▏| 46/50 [00:07<00:00, 6.17it/s]\n 94%|█████████▍| 47/50 [00:07<00:00, 6.17it/s]\n 96%|█████████▌| 48/50 [00:07<00:00, 6.17it/s]\n 98%|█████████▊| 49/50 [00:07<00:00, 6.17it/s]\n100%|██████████| 50/50 [00:08<00:00, 6.17it/s]\n100%|██████████| 50/50 [00:08<00:00, 6.15it/s]", "metrics": { "predict_time": 10.898678, "total_time": 109.414418 }, "output": [ "https://replicate.delivery/pbxt/qXQzb9s7Qu4ACdWZ58dqQgWwdiuPILGtK9axH6GzMmCH1ceIA/out-0.png" ], "started_at": "2023-11-19T03:37:54.332596Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ecahymlb6qqbec34lkiwmjukgq", "cancel": "https://api.replicate.com/v1/predictions/ecahymlb6qqbec34lkiwmjukgq/cancel" }, "version": "4339b367ceed5d9b1b96e29245e3ec367745422b8d3cc9a6b1e83b66f68943d1" }
Generated inUsing seed: 13888 Ensuring enough disk space... Free disk space: 1862720487424 Downloading weights: https://replicate.delivery/pbxt/GID77w3Tdib1PtnqMP3FvBLmk1YNbw1hip2jfZerPRWPMy5RA/trained_model.tar b'Downloaded 186 MB bytes in 0.261s (712 MB/s)\nExtracted 186 MB in 0.050s (3.7 GB/s)\n' Downloaded weights in 0.3919353485107422 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: cat in a forest clearing surrounded by trees in the style of <s0><s1>, clean, simple txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:07, 6.20it/s] 4%|▍ | 2/50 [00:00<00:07, 6.19it/s] 6%|▌ | 3/50 [00:00<00:07, 6.18it/s] 8%|▊ | 4/50 [00:00<00:07, 6.17it/s] 10%|█ | 5/50 [00:00<00:07, 6.17it/s] 12%|█▏ | 6/50 [00:00<00:07, 6.17it/s] 14%|█▍ | 7/50 [00:01<00:06, 6.17it/s] 16%|█▌ | 8/50 [00:01<00:06, 6.16it/s] 18%|█▊ | 9/50 [00:01<00:06, 6.16it/s] 20%|██ | 10/50 [00:01<00:06, 6.16it/s] 22%|██▏ | 11/50 [00:01<00:06, 6.16it/s] 24%|██▍ | 12/50 [00:01<00:06, 6.15it/s] 26%|██▌ | 13/50 [00:02<00:06, 6.15it/s] 28%|██▊ | 14/50 [00:02<00:05, 6.15it/s] 30%|███ | 15/50 [00:02<00:05, 6.15it/s] 32%|███▏ | 16/50 [00:02<00:05, 6.14it/s] 34%|███▍ | 17/50 [00:02<00:05, 6.14it/s] 36%|███▌ | 18/50 [00:02<00:05, 6.14it/s] 38%|███▊ | 19/50 [00:03<00:05, 6.15it/s] 40%|████ | 20/50 [00:03<00:04, 6.15it/s] 42%|████▏ | 21/50 [00:03<00:04, 6.15it/s] 44%|████▍ | 22/50 [00:03<00:04, 6.14it/s] 46%|████▌ | 23/50 [00:03<00:04, 6.14it/s] 48%|████▊ | 24/50 [00:03<00:04, 6.14it/s] 50%|█████ | 25/50 [00:04<00:04, 6.15it/s] 52%|█████▏ | 26/50 [00:04<00:03, 6.15it/s] 54%|█████▍ | 27/50 [00:04<00:03, 6.15it/s] 56%|█████▌ | 28/50 [00:04<00:03, 6.15it/s] 58%|█████▊ | 29/50 [00:04<00:03, 6.15it/s] 60%|██████ | 30/50 [00:04<00:03, 6.14it/s] 62%|██████▏ | 31/50 [00:05<00:03, 6.13it/s] 64%|██████▍ | 32/50 [00:05<00:02, 6.14it/s] 66%|██████▌ | 33/50 [00:05<00:02, 6.14it/s] 68%|██████▊ | 34/50 [00:05<00:02, 6.14it/s] 70%|███████ | 35/50 [00:05<00:02, 6.14it/s] 72%|███████▏ | 36/50 [00:05<00:02, 6.14it/s] 74%|███████▍ | 37/50 [00:06<00:02, 6.13it/s] 76%|███████▌ | 38/50 [00:06<00:01, 6.13it/s] 78%|███████▊ | 39/50 [00:06<00:01, 6.14it/s] 80%|████████ | 40/50 [00:06<00:01, 6.15it/s] 82%|████████▏ | 41/50 [00:06<00:01, 6.16it/s] 84%|████████▍ | 42/50 [00:06<00:01, 6.17it/s] 86%|████████▌ | 43/50 [00:06<00:01, 6.17it/s] 88%|████████▊ | 44/50 [00:07<00:00, 6.17it/s] 90%|█████████ | 45/50 [00:07<00:00, 6.17it/s] 92%|█████████▏| 46/50 [00:07<00:00, 6.17it/s] 94%|█████████▍| 47/50 [00:07<00:00, 6.17it/s] 96%|█████████▌| 48/50 [00:07<00:00, 6.17it/s] 98%|█████████▊| 49/50 [00:07<00:00, 6.17it/s] 100%|██████████| 50/50 [00:08<00:00, 6.17it/s] 100%|██████████| 50/50 [00:08<00:00, 6.15it/s]
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