fofr
/
sdxl-sonic-2-hd
- Public
- 176 runs
-
L40S
- SDXL fine-tune
Prediction
fofr/sdxl-sonic-2-hd:da4ceb19IDrg7aqptblnvwbzrdmdnyuziaaeStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- mask
- null
- seed
- null
- image
- null
- width
- 1152
- height
- 768
- prompt
- A TOK screenshot of a beach level, video game, platformer
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- refine_steps
- null
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- ugly, distorted, repeating patterns, disfigured, text, numbers
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "mask": null, "seed": null, "image": null, "width": 1152, "height": 768, "prompt": "A TOK screenshot of a beach level, video game, platformer", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "refine_steps": null, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "ugly, distorted, repeating patterns, disfigured, text, numbers", "prompt_strength": 0.8, "num_inference_steps": 30 }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 fofr/sdxl-sonic-2-hd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-sonic-2-hd:da4ceb19689e32bba34374d8ff6bc2bac88cd2bf473a6b9f8e6c38fc5dfa0bd0", { input: { width: 1152, height: 768, prompt: "A TOK screenshot of a beach level, video game, platformer", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.8, negative_prompt: "ugly, distorted, repeating patterns, disfigured, text, numbers", prompt_strength: 0.8, num_inference_steps: 30 } } ); 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 fofr/sdxl-sonic-2-hd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-sonic-2-hd:da4ceb19689e32bba34374d8ff6bc2bac88cd2bf473a6b9f8e6c38fc5dfa0bd0", input={ "width": 1152, "height": 768, "prompt": "A TOK screenshot of a beach level, video game, platformer", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.8, "negative_prompt": "ugly, distorted, repeating patterns, disfigured, text, numbers", "prompt_strength": 0.8, "num_inference_steps": 30 } ) 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 fofr/sdxl-sonic-2-hd 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": "da4ceb19689e32bba34374d8ff6bc2bac88cd2bf473a6b9f8e6c38fc5dfa0bd0", "input": { "width": 1152, "height": 768, "prompt": "A TOK screenshot of a beach level, video game, platformer", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "ugly, distorted, repeating patterns, disfigured, text, numbers", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-10-30T23:25:53.889769Z", "created_at": "2023-10-30T23:25:41.848891Z", "data_removed": false, "error": null, "id": "rg7aqptblnvwbzrdmdnyuziaae", "input": { "mask": null, "seed": null, "image": null, "width": 1152, "height": 768, "prompt": "A TOK screenshot of a beach level, video game, platformer", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "refine_steps": null, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "ugly, distorted, repeating patterns, disfigured, text, numbers", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 63627\nEnsuring enough disk space...\nFree disk space: 1526832726016\nDownloading weights: https://pbxt.replicate.delivery/VCyfGxkUGk3LFaJ9keWqbe2kWksLzEFzxgHAhyi7pd85h9mjA/trained_model.tar\nb'Downloaded 186 MB bytes in 0.259s (718 MB/s)\\nExtracted 186 MB in 0.068s (2.7 GB/s)\\n'\nDownloaded weights in 0.43831610679626465 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: A <s0><s1> screenshot of a beach level, video game, platformer\ntxt2img mode\n 0%| | 0/23 [00:00<?, ?it/s]\n 4%|▍ | 1/23 [00:00<00:05, 4.08it/s]\n 9%|▊ | 2/23 [00:00<00:04, 4.22it/s]\n 13%|█▎ | 3/23 [00:00<00:04, 4.26it/s]\n 17%|█▋ | 4/23 [00:00<00:04, 4.28it/s]\n 22%|██▏ | 5/23 [00:01<00:04, 4.29it/s]\n 26%|██▌ | 6/23 [00:01<00:03, 4.29it/s]\n 30%|███ | 7/23 [00:01<00:03, 4.30it/s]\n 35%|███▍ | 8/23 [00:01<00:03, 4.29it/s]\n 39%|███▉ | 9/23 [00:02<00:03, 4.30it/s]\n 43%|████▎ | 10/23 [00:02<00:03, 4.29it/s]\n 48%|████▊ | 11/23 [00:02<00:02, 4.29it/s]\n 52%|█████▏ | 12/23 [00:02<00:02, 4.29it/s]\n 57%|█████▋ | 13/23 [00:03<00:02, 4.29it/s]\n 61%|██████ | 14/23 [00:03<00:02, 4.29it/s]\n 65%|██████▌ | 15/23 [00:03<00:01, 4.29it/s]\n 70%|██████▉ | 16/23 [00:03<00:01, 4.30it/s]\n 74%|███████▍ | 17/23 [00:03<00:01, 4.31it/s]\n 78%|███████▊ | 18/23 [00:04<00:01, 4.31it/s]\n 83%|████████▎ | 19/23 [00:04<00:00, 4.32it/s]\n 87%|████████▋ | 20/23 [00:04<00:00, 4.32it/s]\n 91%|█████████▏| 21/23 [00:04<00:00, 4.32it/s]\n 96%|█████████▌| 22/23 [00:05<00:00, 4.32it/s]\n100%|██████████| 23/23 [00:05<00:00, 4.32it/s]\n100%|██████████| 23/23 [00:05<00:00, 4.30it/s]\n 0%| | 0/7 [00:00<?, ?it/s]\n 14%|█▍ | 1/7 [00:00<00:01, 5.19it/s]\n 29%|██▊ | 2/7 [00:00<00:00, 5.38it/s]\n 43%|████▎ | 3/7 [00:00<00:00, 5.45it/s]\n 57%|█████▋ | 4/7 [00:00<00:00, 5.49it/s]\n 71%|███████▏ | 5/7 [00:00<00:00, 5.50it/s]\n 86%|████████▌ | 6/7 [00:01<00:00, 5.48it/s]\n100%|██████████| 7/7 [00:01<00:00, 5.49it/s]\n100%|██████████| 7/7 [00:01<00:00, 5.46it/s]", "metrics": { "predict_time": 9.136445, "total_time": 12.040878 }, "output": [ "https://pbxt.replicate.delivery/xXiJhxg0rRo5P56QxFiNhSJjYe4LKh4b1wHklvLBFfGB2emjA/out-0.png" ], "started_at": "2023-10-30T23:25:44.753324Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/rg7aqptblnvwbzrdmdnyuziaae", "cancel": "https://api.replicate.com/v1/predictions/rg7aqptblnvwbzrdmdnyuziaae/cancel" }, "version": "da4ceb19689e32bba34374d8ff6bc2bac88cd2bf473a6b9f8e6c38fc5dfa0bd0" }Generated inUsing seed: 63627 Ensuring enough disk space... Free disk space: 1526832726016 Downloading weights: https://pbxt.replicate.delivery/VCyfGxkUGk3LFaJ9keWqbe2kWksLzEFzxgHAhyi7pd85h9mjA/trained_model.tar b'Downloaded 186 MB bytes in 0.259s (718 MB/s)\nExtracted 186 MB in 0.068s (2.7 GB/s)\n' Downloaded weights in 0.43831610679626465 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: A <s0><s1> screenshot of a beach level, video game, platformer txt2img mode 0%| | 0/23 [00:00<?, ?it/s] 4%|▍ | 1/23 [00:00<00:05, 4.08it/s] 9%|▊ | 2/23 [00:00<00:04, 4.22it/s] 13%|█▎ | 3/23 [00:00<00:04, 4.26it/s] 17%|█▋ | 4/23 [00:00<00:04, 4.28it/s] 22%|██▏ | 5/23 [00:01<00:04, 4.29it/s] 26%|██▌ | 6/23 [00:01<00:03, 4.29it/s] 30%|███ | 7/23 [00:01<00:03, 4.30it/s] 35%|███▍ | 8/23 [00:01<00:03, 4.29it/s] 39%|███▉ | 9/23 [00:02<00:03, 4.30it/s] 43%|████▎ | 10/23 [00:02<00:03, 4.29it/s] 48%|████▊ | 11/23 [00:02<00:02, 4.29it/s] 52%|█████▏ | 12/23 [00:02<00:02, 4.29it/s] 57%|█████▋ | 13/23 [00:03<00:02, 4.29it/s] 61%|██████ | 14/23 [00:03<00:02, 4.29it/s] 65%|██████▌ | 15/23 [00:03<00:01, 4.29it/s] 70%|██████▉ | 16/23 [00:03<00:01, 4.30it/s] 74%|███████▍ | 17/23 [00:03<00:01, 4.31it/s] 78%|███████▊ | 18/23 [00:04<00:01, 4.31it/s] 83%|████████▎ | 19/23 [00:04<00:00, 4.32it/s] 87%|████████▋ | 20/23 [00:04<00:00, 4.32it/s] 91%|█████████▏| 21/23 [00:04<00:00, 4.32it/s] 96%|█████████▌| 22/23 [00:05<00:00, 4.32it/s] 100%|██████████| 23/23 [00:05<00:00, 4.32it/s] 100%|██████████| 23/23 [00:05<00:00, 4.30it/s] 0%| | 0/7 [00:00<?, ?it/s] 14%|█▍ | 1/7 [00:00<00:01, 5.19it/s] 29%|██▊ | 2/7 [00:00<00:00, 5.38it/s] 43%|████▎ | 3/7 [00:00<00:00, 5.45it/s] 57%|█████▋ | 4/7 [00:00<00:00, 5.49it/s] 71%|███████▏ | 5/7 [00:00<00:00, 5.50it/s] 86%|████████▌ | 6/7 [00:01<00:00, 5.48it/s] 100%|██████████| 7/7 [00:01<00:00, 5.49it/s] 100%|██████████| 7/7 [00:01<00:00, 5.46it/s]Prediction
fofr/sdxl-sonic-2-hd:da4ceb19IDj566yjdb3zxdo7h6ij5kykusreStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- mask
- null
- seed
- null
- image
- null
- width
- 1152
- height
- 768
- prompt
- A TOK screenshot of a snowy mountain level, video game, platformer
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- refine_steps
- null
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- ugly, distorted, repeating patterns, disfigured, text, numbers, purple
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "mask": null, "seed": null, "image": null, "width": 1152, "height": 768, "prompt": "A TOK screenshot of a snowy mountain level, video game, platformer", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "refine_steps": null, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "ugly, distorted, repeating patterns, disfigured, text, numbers, purple", "prompt_strength": 0.8, "num_inference_steps": 30 }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 fofr/sdxl-sonic-2-hd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-sonic-2-hd:da4ceb19689e32bba34374d8ff6bc2bac88cd2bf473a6b9f8e6c38fc5dfa0bd0", { input: { width: 1152, height: 768, prompt: "A TOK screenshot of a snowy mountain level, video game, platformer", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.8, negative_prompt: "ugly, distorted, repeating patterns, disfigured, text, numbers, purple", prompt_strength: 0.8, num_inference_steps: 30 } } ); 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 fofr/sdxl-sonic-2-hd using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-sonic-2-hd:da4ceb19689e32bba34374d8ff6bc2bac88cd2bf473a6b9f8e6c38fc5dfa0bd0", input={ "width": 1152, "height": 768, "prompt": "A TOK screenshot of a snowy mountain level, video game, platformer", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.8, "negative_prompt": "ugly, distorted, repeating patterns, disfigured, text, numbers, purple", "prompt_strength": 0.8, "num_inference_steps": 30 } ) 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 fofr/sdxl-sonic-2-hd 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": "da4ceb19689e32bba34374d8ff6bc2bac88cd2bf473a6b9f8e6c38fc5dfa0bd0", "input": { "width": 1152, "height": 768, "prompt": "A TOK screenshot of a snowy mountain level, video game, platformer", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "ugly, distorted, repeating patterns, disfigured, text, numbers, purple", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-10-30T23:26:38.880336Z", "created_at": "2023-10-30T23:26:31.144521Z", "data_removed": false, "error": null, "id": "j566yjdb3zxdo7h6ij5kykusre", "input": { "mask": null, "seed": null, "image": null, "width": 1152, "height": 768, "prompt": "A TOK screenshot of a snowy mountain level, video game, platformer", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "refine_steps": null, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.8, "negative_prompt": "ugly, distorted, repeating patterns, disfigured, text, numbers, purple", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 26061\nskipping loading .. weights already loaded\nPrompt: A <s0><s1> screenshot of a snowy mountain level, video game, platformer\ntxt2img mode\n 0%| | 0/23 [00:00<?, ?it/s]\n 4%|▍ | 1/23 [00:00<00:05, 4.34it/s]\n 9%|▊ | 2/23 [00:00<00:04, 4.32it/s]\n 13%|█▎ | 3/23 [00:00<00:04, 4.32it/s]\n 17%|█▋ | 4/23 [00:00<00:04, 4.32it/s]\n 22%|██▏ | 5/23 [00:01<00:04, 4.32it/s]\n 26%|██▌ | 6/23 [00:01<00:03, 4.31it/s]\n 30%|███ | 7/23 [00:01<00:03, 4.31it/s]\n 35%|███▍ | 8/23 [00:01<00:03, 4.31it/s]\n 39%|███▉ | 9/23 [00:02<00:03, 4.31it/s]\n 43%|████▎ | 10/23 [00:02<00:03, 4.31it/s]\n 48%|████▊ | 11/23 [00:02<00:02, 4.32it/s]\n 52%|█████▏ | 12/23 [00:02<00:02, 4.32it/s]\n 57%|█████▋ | 13/23 [00:03<00:02, 4.33it/s]\n 61%|██████ | 14/23 [00:03<00:02, 4.33it/s]\n 65%|██████▌ | 15/23 [00:03<00:01, 4.33it/s]\n 70%|██████▉ | 16/23 [00:03<00:01, 4.33it/s]\n 74%|███████▍ | 17/23 [00:03<00:01, 4.33it/s]\n 78%|███████▊ | 18/23 [00:04<00:01, 4.33it/s]\n 83%|████████▎ | 19/23 [00:04<00:00, 4.33it/s]\n 87%|████████▋ | 20/23 [00:04<00:00, 4.33it/s]\n 91%|█████████▏| 21/23 [00:04<00:00, 4.33it/s]\n 96%|█████████▌| 22/23 [00:05<00:00, 4.33it/s]\n100%|██████████| 23/23 [00:05<00:00, 4.32it/s]\n100%|██████████| 23/23 [00:05<00:00, 4.32it/s]\n 0%| | 0/7 [00:00<?, ?it/s]\n 14%|█▍ | 1/7 [00:00<00:01, 5.58it/s]\n 29%|██▊ | 2/7 [00:00<00:00, 5.55it/s]\n 43%|████▎ | 3/7 [00:00<00:00, 5.54it/s]\n 57%|█████▋ | 4/7 [00:00<00:00, 5.51it/s]\n 71%|███████▏ | 5/7 [00:00<00:00, 5.50it/s]\n 86%|████████▌ | 6/7 [00:01<00:00, 5.50it/s]\n100%|██████████| 7/7 [00:01<00:00, 5.49it/s]\n100%|██████████| 7/7 [00:01<00:00, 5.51it/s]", "metrics": { "predict_time": 7.785567, "total_time": 7.735815 }, "output": [ "https://pbxt.replicate.delivery/GFbe7nEHiCSydSfhOgxJHlYYATjKSs9aDfsmehXfuYo212bOC/out-0.png" ], "started_at": "2023-10-30T23:26:31.094769Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/j566yjdb3zxdo7h6ij5kykusre", "cancel": "https://api.replicate.com/v1/predictions/j566yjdb3zxdo7h6ij5kykusre/cancel" }, "version": "da4ceb19689e32bba34374d8ff6bc2bac88cd2bf473a6b9f8e6c38fc5dfa0bd0" }Generated inUsing seed: 26061 skipping loading .. weights already loaded Prompt: A <s0><s1> screenshot of a snowy mountain level, video game, platformer txt2img mode 0%| | 0/23 [00:00<?, ?it/s] 4%|▍ | 1/23 [00:00<00:05, 4.34it/s] 9%|▊ | 2/23 [00:00<00:04, 4.32it/s] 13%|█▎ | 3/23 [00:00<00:04, 4.32it/s] 17%|█▋ | 4/23 [00:00<00:04, 4.32it/s] 22%|██▏ | 5/23 [00:01<00:04, 4.32it/s] 26%|██▌ | 6/23 [00:01<00:03, 4.31it/s] 30%|███ | 7/23 [00:01<00:03, 4.31it/s] 35%|███▍ | 8/23 [00:01<00:03, 4.31it/s] 39%|███▉ | 9/23 [00:02<00:03, 4.31it/s] 43%|████▎ | 10/23 [00:02<00:03, 4.31it/s] 48%|████▊ | 11/23 [00:02<00:02, 4.32it/s] 52%|█████▏ | 12/23 [00:02<00:02, 4.32it/s] 57%|█████▋ | 13/23 [00:03<00:02, 4.33it/s] 61%|██████ | 14/23 [00:03<00:02, 4.33it/s] 65%|██████▌ | 15/23 [00:03<00:01, 4.33it/s] 70%|██████▉ | 16/23 [00:03<00:01, 4.33it/s] 74%|███████▍ | 17/23 [00:03<00:01, 4.33it/s] 78%|███████▊ | 18/23 [00:04<00:01, 4.33it/s] 83%|████████▎ | 19/23 [00:04<00:00, 4.33it/s] 87%|████████▋ | 20/23 [00:04<00:00, 4.33it/s] 91%|█████████▏| 21/23 [00:04<00:00, 4.33it/s] 96%|█████████▌| 22/23 [00:05<00:00, 4.33it/s] 100%|██████████| 23/23 [00:05<00:00, 4.32it/s] 100%|██████████| 23/23 [00:05<00:00, 4.32it/s] 0%| | 0/7 [00:00<?, ?it/s] 14%|█▍ | 1/7 [00:00<00:01, 5.58it/s] 29%|██▊ | 2/7 [00:00<00:00, 5.55it/s] 43%|████▎ | 3/7 [00:00<00:00, 5.54it/s] 57%|█████▋ | 4/7 [00:00<00:00, 5.51it/s] 71%|███████▏ | 5/7 [00:00<00:00, 5.50it/s] 86%|████████▌ | 6/7 [00:01<00:00, 5.50it/s] 100%|██████████| 7/7 [00:01<00:00, 5.49it/s] 100%|██████████| 7/7 [00:01<00:00, 5.51it/s]
Want to make some of these yourself?
Run this model