fofr
/
sdxl-tng-interior
SDXL fine-tune of Star Trek Next Generation interiors
- Public
- 1.3K runs
-
L40S
Prediction
fofr/sdxl-tng-interior:45f1d0cfIDyz34aztbtgd6x2a3j44myxyyzyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1152
- height
- 768
- prompt
- A photo of an alien corridor in the style of TOK, minimal
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.65
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.95
- negative_prompt
- people, black and white, cluttered, low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1152, "height": 768, "prompt": "A photo of an alien corridor in the style of TOK, minimal", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.65, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "people, black and white, cluttered, low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/sdxl-tng-interior using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-tng-interior:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", { input: { width: 1152, height: 768, prompt: "A photo of an alien corridor in the style of TOK, minimal", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.65, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.95, negative_prompt: "people, black and white, cluttered, low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run fofr/sdxl-tng-interior using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-tng-interior:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", input={ "width": 1152, "height": 768, "prompt": "A photo of an alien corridor in the style of TOK, minimal", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.65, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.95, "negative_prompt": "people, black and white, cluttered, low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/sdxl-tng-interior 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": "45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", "input": { "width": 1152, "height": 768, "prompt": "A photo of an alien corridor in the style of TOK, minimal", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.65, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "people, black and white, cluttered, low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run fofr/sdxl-tng-interior using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/fofr/sdxl-tng-interior@sha256:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f \ -i 'width=1152' \ -i 'height=768' \ -i 'prompt="A photo of an alien corridor in the style of TOK, minimal"' \ -i 'refine="expert_ensemble_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.65' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=false' \ -i 'high_noise_frac=0.95' \ -i 'negative_prompt="people, black and white, cluttered, low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Pull and run fofr/sdxl-tng-interior using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/fofr/sdxl-tng-interior@sha256:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1152, "height": 768, "prompt": "A photo of an alien corridor in the style of TOK, minimal", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.65, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "people, black and white, cluttered, low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2023-08-27T21:08:16.805394Z", "created_at": "2023-08-27T21:07:17.795428Z", "data_removed": false, "error": null, "id": "yz34aztbtgd6x2a3j44myxyyzy", "input": { "width": 1152, "height": 768, "prompt": "A photo of an alien corridor in the style of TOK, minimal", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.65, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "people, black and white, cluttered, low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 45977\nPrompt: A photo of an alien corridor in the style of <s0><s1>, minimal\ntxt2img mode\n 0%| | 0/47 [00:00<?, ?it/s]\n 2%|▏ | 1/47 [00:00<00:36, 1.25it/s]\n 4%|▍ | 2/47 [00:01<00:20, 2.15it/s]\n 6%|▋ | 3/47 [00:01<00:15, 2.81it/s]\n 9%|▊ | 4/47 [00:01<00:13, 3.27it/s]\n 11%|█ | 5/47 [00:01<00:11, 3.59it/s]\n 13%|█▎ | 6/47 [00:01<00:10, 3.82it/s]\n 15%|█▍ | 7/47 [00:02<00:10, 3.98it/s]\n 17%|█▋ | 8/47 [00:02<00:09, 4.09it/s]\n 19%|█▉ | 9/47 [00:02<00:09, 4.17it/s]\n 21%|██▏ | 10/47 [00:02<00:08, 4.23it/s]\n 23%|██▎ | 11/47 [00:03<00:08, 4.27it/s]\n 26%|██▌ | 12/47 [00:03<00:08, 4.29it/s]\n 28%|██▊ | 13/47 [00:03<00:07, 4.31it/s]\n 30%|██▉ | 14/47 [00:03<00:07, 4.32it/s]\n 32%|███▏ | 15/47 [00:04<00:07, 4.33it/s]\n 34%|███▍ | 16/47 [00:04<00:07, 4.34it/s]\n 36%|███▌ | 17/47 [00:04<00:06, 4.34it/s]\n 38%|███▊ | 18/47 [00:04<00:06, 4.35it/s]\n 40%|████ | 19/47 [00:04<00:06, 4.35it/s]\n 43%|████▎ | 20/47 [00:05<00:06, 4.35it/s]\n 45%|████▍ | 21/47 [00:05<00:05, 4.35it/s]\n 47%|████▋ | 22/47 [00:05<00:05, 4.35it/s]\n 49%|████▉ | 23/47 [00:05<00:05, 4.35it/s]\n 51%|█████ | 24/47 [00:06<00:05, 4.35it/s]\n 53%|█████▎ | 25/47 [00:06<00:05, 4.35it/s]\n 55%|█████▌ | 26/47 [00:06<00:04, 4.35it/s]\n 57%|█████▋ | 27/47 [00:06<00:04, 4.35it/s]\n 60%|█████▉ | 28/47 [00:07<00:04, 4.35it/s]\n 62%|██████▏ | 29/47 [00:07<00:04, 4.34it/s]\n 64%|██████▍ | 30/47 [00:07<00:03, 4.34it/s]\n 66%|██████▌ | 31/47 [00:07<00:03, 4.35it/s]\n 68%|██████▊ | 32/47 [00:07<00:03, 4.36it/s]\n 70%|███████ | 33/47 [00:08<00:03, 4.36it/s]\n 72%|███████▏ | 34/47 [00:08<00:02, 4.36it/s]\n 74%|███████▍ | 35/47 [00:08<00:02, 4.37it/s]\n 77%|███████▋ | 36/47 [00:08<00:02, 4.37it/s]\n 79%|███████▊ | 37/47 [00:09<00:02, 4.37it/s]\n 81%|████████ | 38/47 [00:09<00:02, 4.37it/s]\n 83%|████████▎ | 39/47 [00:09<00:01, 4.37it/s]\n 85%|████████▌ | 40/47 [00:09<00:01, 4.37it/s]\n 87%|████████▋ | 41/47 [00:09<00:01, 4.37it/s]\n 89%|████████▉ | 42/47 [00:10<00:01, 4.37it/s]\n 91%|█████████▏| 43/47 [00:10<00:00, 4.37it/s]\n 94%|█████████▎| 44/47 [00:10<00:00, 4.37it/s]\n 96%|█████████▌| 45/47 [00:10<00:00, 4.37it/s]\n 98%|█████████▊| 46/47 [00:11<00:00, 4.37it/s]\n100%|██████████| 47/47 [00:11<00:00, 4.37it/s]\n100%|██████████| 47/47 [00:11<00:00, 4.14it/s]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:00, 5.34it/s]\n 67%|██████▋ | 2/3 [00:00<00:00, 5.50it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.55it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.52it/s]", "metrics": { "predict_time": 13.730508, "total_time": 59.009966 }, "output": [ "https://replicate.delivery/pbxt/CKJKIWwj2TIgIBQfFxWf43LF8FovHfUr75SM9CHSBxDBqt8iA/out-0.png" ], "started_at": "2023-08-27T21:08:03.074886Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/yz34aztbtgd6x2a3j44myxyyzy", "cancel": "https://api.replicate.com/v1/predictions/yz34aztbtgd6x2a3j44myxyyzy/cancel" }, "version": "45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f" }
Generated inUsing seed: 45977 Prompt: A photo of an alien corridor in the style of <s0><s1>, minimal txt2img mode 0%| | 0/47 [00:00<?, ?it/s] 2%|▏ | 1/47 [00:00<00:36, 1.25it/s] 4%|▍ | 2/47 [00:01<00:20, 2.15it/s] 6%|▋ | 3/47 [00:01<00:15, 2.81it/s] 9%|▊ | 4/47 [00:01<00:13, 3.27it/s] 11%|█ | 5/47 [00:01<00:11, 3.59it/s] 13%|█▎ | 6/47 [00:01<00:10, 3.82it/s] 15%|█▍ | 7/47 [00:02<00:10, 3.98it/s] 17%|█▋ | 8/47 [00:02<00:09, 4.09it/s] 19%|█▉ | 9/47 [00:02<00:09, 4.17it/s] 21%|██▏ | 10/47 [00:02<00:08, 4.23it/s] 23%|██▎ | 11/47 [00:03<00:08, 4.27it/s] 26%|██▌ | 12/47 [00:03<00:08, 4.29it/s] 28%|██▊ | 13/47 [00:03<00:07, 4.31it/s] 30%|██▉ | 14/47 [00:03<00:07, 4.32it/s] 32%|███▏ | 15/47 [00:04<00:07, 4.33it/s] 34%|███▍ | 16/47 [00:04<00:07, 4.34it/s] 36%|███▌ | 17/47 [00:04<00:06, 4.34it/s] 38%|███▊ | 18/47 [00:04<00:06, 4.35it/s] 40%|████ | 19/47 [00:04<00:06, 4.35it/s] 43%|████▎ | 20/47 [00:05<00:06, 4.35it/s] 45%|████▍ | 21/47 [00:05<00:05, 4.35it/s] 47%|████▋ | 22/47 [00:05<00:05, 4.35it/s] 49%|████▉ | 23/47 [00:05<00:05, 4.35it/s] 51%|█████ | 24/47 [00:06<00:05, 4.35it/s] 53%|█████▎ | 25/47 [00:06<00:05, 4.35it/s] 55%|█████▌ | 26/47 [00:06<00:04, 4.35it/s] 57%|█████▋ | 27/47 [00:06<00:04, 4.35it/s] 60%|█████▉ | 28/47 [00:07<00:04, 4.35it/s] 62%|██████▏ | 29/47 [00:07<00:04, 4.34it/s] 64%|██████▍ | 30/47 [00:07<00:03, 4.34it/s] 66%|██████▌ | 31/47 [00:07<00:03, 4.35it/s] 68%|██████▊ | 32/47 [00:07<00:03, 4.36it/s] 70%|███████ | 33/47 [00:08<00:03, 4.36it/s] 72%|███████▏ | 34/47 [00:08<00:02, 4.36it/s] 74%|███████▍ | 35/47 [00:08<00:02, 4.37it/s] 77%|███████▋ | 36/47 [00:08<00:02, 4.37it/s] 79%|███████▊ | 37/47 [00:09<00:02, 4.37it/s] 81%|████████ | 38/47 [00:09<00:02, 4.37it/s] 83%|████████▎ | 39/47 [00:09<00:01, 4.37it/s] 85%|████████▌ | 40/47 [00:09<00:01, 4.37it/s] 87%|████████▋ | 41/47 [00:09<00:01, 4.37it/s] 89%|████████▉ | 42/47 [00:10<00:01, 4.37it/s] 91%|█████████▏| 43/47 [00:10<00:00, 4.37it/s] 94%|█████████▎| 44/47 [00:10<00:00, 4.37it/s] 96%|█████████▌| 45/47 [00:10<00:00, 4.37it/s] 98%|█████████▊| 46/47 [00:11<00:00, 4.37it/s] 100%|██████████| 47/47 [00:11<00:00, 4.37it/s] 100%|██████████| 47/47 [00:11<00:00, 4.14it/s] 0%| | 0/3 [00:00<?, ?it/s] 33%|███▎ | 1/3 [00:00<00:00, 5.34it/s] 67%|██████▋ | 2/3 [00:00<00:00, 5.50it/s] 100%|██████████| 3/3 [00:00<00:00, 5.55it/s] 100%|██████████| 3/3 [00:00<00:00, 5.52it/s]
Prediction
fofr/sdxl-tng-interior:45f1d0cfIDgjgn6qlbmwbbgzkzcpozogg6wyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1152
- height
- 768
- prompt
- Am unreal engine render in the style of TOK, a portrait of a woman, starfleet uniform, detailed, high resolution, dynamic, action, bokeh, sparks
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.9
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.95
- negative_prompt
- low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a portrait of a woman, starfleet uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/sdxl-tng-interior using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-tng-interior:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", { input: { width: 1152, height: 768, prompt: "Am unreal engine render in the style of TOK, a portrait of a woman, starfleet uniform, detailed, high resolution, dynamic, action, bokeh, sparks", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.9, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.95, negative_prompt: "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run fofr/sdxl-tng-interior using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-tng-interior:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", input={ "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a portrait of a woman, starfleet uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/sdxl-tng-interior 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": "45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", "input": { "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a portrait of a woman, starfleet uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run fofr/sdxl-tng-interior using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/fofr/sdxl-tng-interior@sha256:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f \ -i 'width=1152' \ -i 'height=768' \ -i 'prompt="Am unreal engine render in the style of TOK, a portrait of a woman, starfleet uniform, detailed, high resolution, dynamic, action, bokeh, sparks"' \ -i 'refine="expert_ensemble_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.9' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=false' \ -i 'high_noise_frac=0.95' \ -i 'negative_prompt="low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Pull and run fofr/sdxl-tng-interior using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/fofr/sdxl-tng-interior@sha256:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a portrait of a woman, starfleet uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2023-08-27T21:20:50.361501Z", "created_at": "2023-08-27T21:20:32.005737Z", "data_removed": false, "error": null, "id": "gjgn6qlbmwbbgzkzcpozogg6wy", "input": { "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a portrait of a woman, starfleet uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 9705\nPrompt: Am unreal engine render in the style of <s0><s1>, a portrait of a woman, starfleet uniform, detailed, high resolution, dynamic, action, bokeh, sparks\ntxt2img mode\n 0%| | 0/47 [00:00<?, ?it/s]\n 2%|▏ | 1/47 [00:00<00:10, 4.32it/s]\n 4%|▍ | 2/47 [00:00<00:10, 4.31it/s]\n 6%|▋ | 3/47 [00:00<00:10, 4.30it/s]\n 9%|▊ | 4/47 [00:00<00:10, 4.30it/s]\n 11%|█ | 5/47 [00:01<00:09, 4.28it/s]\n 13%|█▎ | 6/47 [00:01<00:09, 4.28it/s]\n 15%|█▍ | 7/47 [00:01<00:09, 4.29it/s]\n 17%|█▋ | 8/47 [00:01<00:09, 4.28it/s]\n 19%|█▉ | 9/47 [00:02<00:08, 4.27it/s]\n 21%|██▏ | 10/47 [00:02<00:08, 4.28it/s]\n 23%|██▎ | 11/47 [00:02<00:08, 4.28it/s]\n 26%|██▌ | 12/47 [00:02<00:08, 4.28it/s]\n 28%|██▊ | 13/47 [00:03<00:07, 4.27it/s]\n 30%|██▉ | 14/47 [00:03<00:07, 4.27it/s]\n 32%|███▏ | 15/47 [00:03<00:07, 4.27it/s]\n 34%|███▍ | 16/47 [00:03<00:07, 4.27it/s]\n 36%|███▌ | 17/47 [00:03<00:07, 4.28it/s]\n 38%|███▊ | 18/47 [00:04<00:06, 4.27it/s]\n 40%|████ | 19/47 [00:04<00:06, 4.26it/s]\n 43%|████▎ | 20/47 [00:04<00:06, 4.26it/s]\n 45%|████▍ | 21/47 [00:04<00:06, 4.27it/s]\n 47%|████▋ | 22/47 [00:05<00:05, 4.26it/s]\n 49%|████▉ | 23/47 [00:05<00:05, 4.27it/s]\n 51%|█████ | 24/47 [00:05<00:05, 4.26it/s]\n 53%|█████▎ | 25/47 [00:05<00:05, 4.27it/s]\n 55%|█████▌ | 26/47 [00:06<00:04, 4.27it/s]\n 57%|█████▋ | 27/47 [00:06<00:04, 4.27it/s]\n 60%|█████▉ | 28/47 [00:06<00:04, 4.27it/s]\n 62%|██████▏ | 29/47 [00:06<00:04, 4.27it/s]\n 64%|██████▍ | 30/47 [00:07<00:03, 4.27it/s]\n 66%|██████▌ | 31/47 [00:07<00:03, 4.27it/s]\n 68%|██████▊ | 32/47 [00:07<00:03, 4.28it/s]\n 70%|███████ | 33/47 [00:07<00:03, 4.27it/s]\n 72%|███████▏ | 34/47 [00:07<00:03, 4.27it/s]\n 74%|███████▍ | 35/47 [00:08<00:02, 4.27it/s]\n 77%|███████▋ | 36/47 [00:08<00:02, 4.27it/s]\n 79%|███████▊ | 37/47 [00:08<00:02, 4.27it/s]\n 81%|████████ | 38/47 [00:08<00:02, 4.27it/s]\n 83%|████████▎ | 39/47 [00:09<00:01, 4.27it/s]\n 85%|████████▌ | 40/47 [00:09<00:01, 4.27it/s]\n 87%|████████▋ | 41/47 [00:09<00:01, 4.27it/s]\n 89%|████████▉ | 42/47 [00:09<00:01, 4.27it/s]\n 91%|█████████▏| 43/47 [00:10<00:00, 4.27it/s]\n 94%|█████████▎| 44/47 [00:10<00:00, 4.27it/s]\n 96%|█████████▌| 45/47 [00:10<00:00, 4.27it/s]\n 98%|█████████▊| 46/47 [00:10<00:00, 4.27it/s]\n100%|██████████| 47/47 [00:10<00:00, 4.27it/s]\n100%|██████████| 47/47 [00:10<00:00, 4.27it/s]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:00, 5.55it/s]\n 67%|██████▋ | 2/3 [00:00<00:00, 5.52it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.52it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.52it/s]", "metrics": { "predict_time": 13.250729, "total_time": 18.355764 }, "output": [ "https://replicate.delivery/pbxt/nZA91cH2bU4RMdkpINdJMtjVZBsSezEFWHWq8IVtuJrYgLvIA/out-0.png" ], "started_at": "2023-08-27T21:20:37.110772Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/gjgn6qlbmwbbgzkzcpozogg6wy", "cancel": "https://api.replicate.com/v1/predictions/gjgn6qlbmwbbgzkzcpozogg6wy/cancel" }, "version": "45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f" }
Generated inUsing seed: 9705 Prompt: Am unreal engine render in the style of <s0><s1>, a portrait of a woman, starfleet uniform, detailed, high resolution, dynamic, action, bokeh, sparks txt2img mode 0%| | 0/47 [00:00<?, ?it/s] 2%|▏ | 1/47 [00:00<00:10, 4.32it/s] 4%|▍ | 2/47 [00:00<00:10, 4.31it/s] 6%|▋ | 3/47 [00:00<00:10, 4.30it/s] 9%|▊ | 4/47 [00:00<00:10, 4.30it/s] 11%|█ | 5/47 [00:01<00:09, 4.28it/s] 13%|█▎ | 6/47 [00:01<00:09, 4.28it/s] 15%|█▍ | 7/47 [00:01<00:09, 4.29it/s] 17%|█▋ | 8/47 [00:01<00:09, 4.28it/s] 19%|█▉ | 9/47 [00:02<00:08, 4.27it/s] 21%|██▏ | 10/47 [00:02<00:08, 4.28it/s] 23%|██▎ | 11/47 [00:02<00:08, 4.28it/s] 26%|██▌ | 12/47 [00:02<00:08, 4.28it/s] 28%|██▊ | 13/47 [00:03<00:07, 4.27it/s] 30%|██▉ | 14/47 [00:03<00:07, 4.27it/s] 32%|███▏ | 15/47 [00:03<00:07, 4.27it/s] 34%|███▍ | 16/47 [00:03<00:07, 4.27it/s] 36%|███▌ | 17/47 [00:03<00:07, 4.28it/s] 38%|███▊ | 18/47 [00:04<00:06, 4.27it/s] 40%|████ | 19/47 [00:04<00:06, 4.26it/s] 43%|████▎ | 20/47 [00:04<00:06, 4.26it/s] 45%|████▍ | 21/47 [00:04<00:06, 4.27it/s] 47%|████▋ | 22/47 [00:05<00:05, 4.26it/s] 49%|████▉ | 23/47 [00:05<00:05, 4.27it/s] 51%|█████ | 24/47 [00:05<00:05, 4.26it/s] 53%|█████▎ | 25/47 [00:05<00:05, 4.27it/s] 55%|█████▌ | 26/47 [00:06<00:04, 4.27it/s] 57%|█████▋ | 27/47 [00:06<00:04, 4.27it/s] 60%|█████▉ | 28/47 [00:06<00:04, 4.27it/s] 62%|██████▏ | 29/47 [00:06<00:04, 4.27it/s] 64%|██████▍ | 30/47 [00:07<00:03, 4.27it/s] 66%|██████▌ | 31/47 [00:07<00:03, 4.27it/s] 68%|██████▊ | 32/47 [00:07<00:03, 4.28it/s] 70%|███████ | 33/47 [00:07<00:03, 4.27it/s] 72%|███████▏ | 34/47 [00:07<00:03, 4.27it/s] 74%|███████▍ | 35/47 [00:08<00:02, 4.27it/s] 77%|███████▋ | 36/47 [00:08<00:02, 4.27it/s] 79%|███████▊ | 37/47 [00:08<00:02, 4.27it/s] 81%|████████ | 38/47 [00:08<00:02, 4.27it/s] 83%|████████▎ | 39/47 [00:09<00:01, 4.27it/s] 85%|████████▌ | 40/47 [00:09<00:01, 4.27it/s] 87%|████████▋ | 41/47 [00:09<00:01, 4.27it/s] 89%|████████▉ | 42/47 [00:09<00:01, 4.27it/s] 91%|█████████▏| 43/47 [00:10<00:00, 4.27it/s] 94%|█████████▎| 44/47 [00:10<00:00, 4.27it/s] 96%|█████████▌| 45/47 [00:10<00:00, 4.27it/s] 98%|█████████▊| 46/47 [00:10<00:00, 4.27it/s] 100%|██████████| 47/47 [00:10<00:00, 4.27it/s] 100%|██████████| 47/47 [00:10<00:00, 4.27it/s] 0%| | 0/3 [00:00<?, ?it/s] 33%|███▎ | 1/3 [00:00<00:00, 5.55it/s] 67%|██████▋ | 2/3 [00:00<00:00, 5.52it/s] 100%|██████████| 3/3 [00:00<00:00, 5.52it/s] 100%|██████████| 3/3 [00:00<00:00, 5.52it/s]
Prediction
fofr/sdxl-tng-interior:45f1d0cfIDz3x7y53bmo5cz7mjkjtz2gttvuStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1152
- height
- 768
- prompt
- Am unreal engine render in the style of TOK, a portrait of a woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.9
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.95
- negative_prompt
- low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a portrait of a woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/sdxl-tng-interior using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-tng-interior:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", { input: { width: 1152, height: 768, prompt: "Am unreal engine render in the style of TOK, a portrait of a woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.9, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.95, negative_prompt: "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run fofr/sdxl-tng-interior using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-tng-interior:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", input={ "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a portrait of a woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/sdxl-tng-interior 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": "45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", "input": { "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a portrait of a woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run fofr/sdxl-tng-interior using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/fofr/sdxl-tng-interior@sha256:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f \ -i 'width=1152' \ -i 'height=768' \ -i 'prompt="Am unreal engine render in the style of TOK, a portrait of a woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks"' \ -i 'refine="expert_ensemble_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.9' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=false' \ -i 'high_noise_frac=0.95' \ -i 'negative_prompt="low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Pull and run fofr/sdxl-tng-interior using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/fofr/sdxl-tng-interior@sha256:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a portrait of a woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2023-08-27T21:23:43.545099Z", "created_at": "2023-08-27T21:23:20.730985Z", "data_removed": false, "error": null, "id": "z3x7y53bmo5cz7mjkjtz2gttvu", "input": { "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a portrait of a woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 21635\nPrompt: Am unreal engine render in the style of <s0><s1>, a portrait of a woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks\ntxt2img mode\n 0%| | 0/47 [00:00<?, ?it/s]\n 2%|▏ | 1/47 [00:00<00:10, 4.33it/s]\n 4%|▍ | 2/47 [00:00<00:10, 4.31it/s]\n 6%|▋ | 3/47 [00:00<00:10, 4.31it/s]\n 9%|▊ | 4/47 [00:00<00:10, 4.29it/s]\n 11%|█ | 5/47 [00:01<00:09, 4.27it/s]\n 13%|█▎ | 6/47 [00:01<00:09, 4.28it/s]\n 15%|█▍ | 7/47 [00:01<00:09, 4.28it/s]\n 17%|█▋ | 8/47 [00:01<00:09, 4.28it/s]\n 19%|█▉ | 9/47 [00:02<00:08, 4.26it/s]\n 21%|██▏ | 10/47 [00:02<00:08, 4.27it/s]\n 23%|██▎ | 11/47 [00:02<00:08, 4.27it/s]\n 26%|██▌ | 12/47 [00:02<00:08, 4.27it/s]\n 28%|██▊ | 13/47 [00:03<00:07, 4.27it/s]\n 30%|██▉ | 14/47 [00:03<00:07, 4.27it/s]\n 32%|███▏ | 15/47 [00:03<00:07, 4.27it/s]\n 34%|███▍ | 16/47 [00:03<00:07, 4.27it/s]\n 36%|███▌ | 17/47 [00:03<00:07, 4.27it/s]\n 38%|███▊ | 18/47 [00:04<00:06, 4.27it/s]\n 40%|████ | 19/47 [00:04<00:06, 4.27it/s]\n 43%|████▎ | 20/47 [00:04<00:06, 4.27it/s]\n 45%|████▍ | 21/47 [00:04<00:06, 4.27it/s]\n 47%|████▋ | 22/47 [00:05<00:05, 4.27it/s]\n 49%|████▉ | 23/47 [00:05<00:05, 4.27it/s]\n 51%|█████ | 24/47 [00:05<00:05, 4.27it/s]\n 53%|█████▎ | 25/47 [00:05<00:05, 4.27it/s]\n 55%|█████▌ | 26/47 [00:06<00:04, 4.27it/s]\n 57%|█████▋ | 27/47 [00:06<00:04, 4.27it/s]\n 60%|█████▉ | 28/47 [00:06<00:04, 4.27it/s]\n 62%|██████▏ | 29/47 [00:06<00:04, 4.27it/s]\n 64%|██████▍ | 30/47 [00:07<00:03, 4.27it/s]\n 66%|██████▌ | 31/47 [00:07<00:03, 4.27it/s]\n 68%|██████▊ | 32/47 [00:07<00:03, 4.27it/s]\n 70%|███████ | 33/47 [00:07<00:03, 4.27it/s]\n 72%|███████▏ | 34/47 [00:07<00:03, 4.27it/s]\n 74%|███████▍ | 35/47 [00:08<00:02, 4.27it/s]\n 77%|███████▋ | 36/47 [00:08<00:02, 4.27it/s]\n 79%|███████▊ | 37/47 [00:08<00:02, 4.26it/s]\n 81%|████████ | 38/47 [00:08<00:02, 4.26it/s]\n 83%|████████▎ | 39/47 [00:09<00:01, 4.27it/s]\n 85%|████████▌ | 40/47 [00:09<00:01, 4.27it/s]\n 87%|████████▋ | 41/47 [00:09<00:01, 4.27it/s]\n 89%|████████▉ | 42/47 [00:09<00:01, 4.27it/s]\n 91%|█████████▏| 43/47 [00:10<00:00, 4.27it/s]\n 94%|█████████▎| 44/47 [00:10<00:00, 4.27it/s]\n 96%|█████████▌| 45/47 [00:10<00:00, 4.27it/s]\n 98%|█████████▊| 46/47 [00:10<00:00, 4.27it/s]\n100%|██████████| 47/47 [00:11<00:00, 4.27it/s]\n100%|██████████| 47/47 [00:11<00:00, 4.27it/s]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:00, 5.54it/s]\n 67%|██████▋ | 2/3 [00:00<00:00, 5.51it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.49it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.50it/s]", "metrics": { "predict_time": 13.252569, "total_time": 22.814114 }, "output": [ "https://replicate.delivery/pbxt/WNVdCbDb1MKSOV7uwX9aiTuSXTOd7clAnBqfp4S4LmdvhLvIA/out-0.png" ], "started_at": "2023-08-27T21:23:30.292530Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/z3x7y53bmo5cz7mjkjtz2gttvu", "cancel": "https://api.replicate.com/v1/predictions/z3x7y53bmo5cz7mjkjtz2gttvu/cancel" }, "version": "45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f" }
Generated inUsing seed: 21635 Prompt: Am unreal engine render in the style of <s0><s1>, a portrait of a woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks txt2img mode 0%| | 0/47 [00:00<?, ?it/s] 2%|▏ | 1/47 [00:00<00:10, 4.33it/s] 4%|▍ | 2/47 [00:00<00:10, 4.31it/s] 6%|▋ | 3/47 [00:00<00:10, 4.31it/s] 9%|▊ | 4/47 [00:00<00:10, 4.29it/s] 11%|█ | 5/47 [00:01<00:09, 4.27it/s] 13%|█▎ | 6/47 [00:01<00:09, 4.28it/s] 15%|█▍ | 7/47 [00:01<00:09, 4.28it/s] 17%|█▋ | 8/47 [00:01<00:09, 4.28it/s] 19%|█▉ | 9/47 [00:02<00:08, 4.26it/s] 21%|██▏ | 10/47 [00:02<00:08, 4.27it/s] 23%|██▎ | 11/47 [00:02<00:08, 4.27it/s] 26%|██▌ | 12/47 [00:02<00:08, 4.27it/s] 28%|██▊ | 13/47 [00:03<00:07, 4.27it/s] 30%|██▉ | 14/47 [00:03<00:07, 4.27it/s] 32%|███▏ | 15/47 [00:03<00:07, 4.27it/s] 34%|███▍ | 16/47 [00:03<00:07, 4.27it/s] 36%|███▌ | 17/47 [00:03<00:07, 4.27it/s] 38%|███▊ | 18/47 [00:04<00:06, 4.27it/s] 40%|████ | 19/47 [00:04<00:06, 4.27it/s] 43%|████▎ | 20/47 [00:04<00:06, 4.27it/s] 45%|████▍ | 21/47 [00:04<00:06, 4.27it/s] 47%|████▋ | 22/47 [00:05<00:05, 4.27it/s] 49%|████▉ | 23/47 [00:05<00:05, 4.27it/s] 51%|█████ | 24/47 [00:05<00:05, 4.27it/s] 53%|█████▎ | 25/47 [00:05<00:05, 4.27it/s] 55%|█████▌ | 26/47 [00:06<00:04, 4.27it/s] 57%|█████▋ | 27/47 [00:06<00:04, 4.27it/s] 60%|█████▉ | 28/47 [00:06<00:04, 4.27it/s] 62%|██████▏ | 29/47 [00:06<00:04, 4.27it/s] 64%|██████▍ | 30/47 [00:07<00:03, 4.27it/s] 66%|██████▌ | 31/47 [00:07<00:03, 4.27it/s] 68%|██████▊ | 32/47 [00:07<00:03, 4.27it/s] 70%|███████ | 33/47 [00:07<00:03, 4.27it/s] 72%|███████▏ | 34/47 [00:07<00:03, 4.27it/s] 74%|███████▍ | 35/47 [00:08<00:02, 4.27it/s] 77%|███████▋ | 36/47 [00:08<00:02, 4.27it/s] 79%|███████▊ | 37/47 [00:08<00:02, 4.26it/s] 81%|████████ | 38/47 [00:08<00:02, 4.26it/s] 83%|████████▎ | 39/47 [00:09<00:01, 4.27it/s] 85%|████████▌ | 40/47 [00:09<00:01, 4.27it/s] 87%|████████▋ | 41/47 [00:09<00:01, 4.27it/s] 89%|████████▉ | 42/47 [00:09<00:01, 4.27it/s] 91%|█████████▏| 43/47 [00:10<00:00, 4.27it/s] 94%|█████████▎| 44/47 [00:10<00:00, 4.27it/s] 96%|█████████▌| 45/47 [00:10<00:00, 4.27it/s] 98%|█████████▊| 46/47 [00:10<00:00, 4.27it/s] 100%|██████████| 47/47 [00:11<00:00, 4.27it/s] 100%|██████████| 47/47 [00:11<00:00, 4.27it/s] 0%| | 0/3 [00:00<?, ?it/s] 33%|███▎ | 1/3 [00:00<00:00, 5.54it/s] 67%|██████▋ | 2/3 [00:00<00:00, 5.51it/s] 100%|██████████| 3/3 [00:00<00:00, 5.49it/s] 100%|██████████| 3/3 [00:00<00:00, 5.50it/s]
Prediction
fofr/sdxl-tng-interior:45f1d0cfID3orytllbjdnb36rlgrbfhmj4deStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1152
- height
- 768
- prompt
- A photo in the style of TOK, interior, house - sustainable, minimalist, organic, light-filled, dynamic, efficient, autonomous, connected, harmonious, innovative, detailed, 8k, high resolution, sharp focus
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.85
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.95
- negative_prompt
- low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1152, "height": 768, "prompt": "A photo in the style of TOK, interior, house - sustainable, minimalist, organic, light-filled, dynamic, efficient, autonomous, connected, harmonious, innovative, detailed, 8k, high resolution, sharp focus", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.85, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/sdxl-tng-interior using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-tng-interior:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", { input: { width: 1152, height: 768, prompt: "A photo in the style of TOK, interior, house - sustainable, minimalist, organic, light-filled, dynamic, efficient, autonomous, connected, harmonious, innovative, detailed, 8k, high resolution, sharp focus", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.85, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.95, negative_prompt: "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run fofr/sdxl-tng-interior using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-tng-interior:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", input={ "width": 1152, "height": 768, "prompt": "A photo in the style of TOK, interior, house - sustainable, minimalist, organic, light-filled, dynamic, efficient, autonomous, connected, harmonious, innovative, detailed, 8k, high resolution, sharp focus", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.85, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/sdxl-tng-interior 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": "45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", "input": { "width": 1152, "height": 768, "prompt": "A photo in the style of TOK, interior, house - sustainable, minimalist, organic, light-filled, dynamic, efficient, autonomous, connected, harmonious, innovative, detailed, 8k, high resolution, sharp focus", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.85, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run fofr/sdxl-tng-interior using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/fofr/sdxl-tng-interior@sha256:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f \ -i 'width=1152' \ -i 'height=768' \ -i 'prompt="A photo in the style of TOK, interior, house - sustainable, minimalist, organic, light-filled, dynamic, efficient, autonomous, connected, harmonious, innovative, detailed, 8k, high resolution, sharp focus"' \ -i 'refine="expert_ensemble_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.85' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=false' \ -i 'high_noise_frac=0.95' \ -i 'negative_prompt="low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Pull and run fofr/sdxl-tng-interior using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/fofr/sdxl-tng-interior@sha256:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1152, "height": 768, "prompt": "A photo in the style of TOK, interior, house - sustainable, minimalist, organic, light-filled, dynamic, efficient, autonomous, connected, harmonious, innovative, detailed, 8k, high resolution, sharp focus", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.85, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2023-08-27T21:03:50.413559Z", "created_at": "2023-08-27T21:03:37.264183Z", "data_removed": false, "error": null, "id": "3orytllbjdnb36rlgrbfhmj4de", "input": { "width": 1152, "height": 768, "prompt": "A photo in the style of TOK, interior, house - sustainable, minimalist, organic, light-filled, dynamic, efficient, autonomous, connected, harmonious, innovative, detailed, 8k, high resolution, sharp focus", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.85, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 14896\nPrompt: A photo in the style of <s0><s1>, interior, house - sustainable, minimalist, organic, light-filled, dynamic, efficient, autonomous, connected, harmonious, innovative, detailed, 8k, high resolution, sharp focus\ntxt2img mode\n 0%| | 0/47 [00:00<?, ?it/s]\n 2%|▏ | 1/47 [00:00<00:10, 4.35it/s]\n 4%|▍ | 2/47 [00:00<00:10, 4.34it/s]\n 6%|▋ | 3/47 [00:00<00:10, 4.34it/s]\n 9%|▊ | 4/47 [00:00<00:09, 4.34it/s]\n 11%|█ | 5/47 [00:01<00:09, 4.33it/s]\n 13%|█▎ | 6/47 [00:01<00:09, 4.33it/s]\n 15%|█▍ | 7/47 [00:01<00:09, 4.33it/s]\n 17%|█▋ | 8/47 [00:01<00:09, 4.33it/s]\n 19%|█▉ | 9/47 [00:02<00:08, 4.33it/s]\n 21%|██▏ | 10/47 [00:02<00:08, 4.33it/s]\n 23%|██▎ | 11/47 [00:02<00:08, 4.32it/s]\n 26%|██▌ | 12/47 [00:02<00:08, 4.33it/s]\n 28%|██▊ | 13/47 [00:03<00:07, 4.32it/s]\n 30%|██▉ | 14/47 [00:03<00:07, 4.32it/s]\n 32%|███▏ | 15/47 [00:03<00:07, 4.32it/s]\n 34%|███▍ | 16/47 [00:03<00:07, 4.33it/s]\n 36%|███▌ | 17/47 [00:03<00:06, 4.33it/s]\n 38%|███▊ | 18/47 [00:04<00:06, 4.32it/s]\n 40%|████ | 19/47 [00:04<00:06, 4.32it/s]\n 43%|████▎ | 20/47 [00:04<00:06, 4.32it/s]\n 45%|████▍ | 21/47 [00:04<00:06, 4.32it/s]\n 47%|████▋ | 22/47 [00:05<00:05, 4.32it/s]\n 49%|████▉ | 23/47 [00:05<00:05, 4.32it/s]\n 51%|█████ | 24/47 [00:05<00:05, 4.32it/s]\n 53%|█████▎ | 25/47 [00:05<00:05, 4.31it/s]\n 55%|█████▌ | 26/47 [00:06<00:04, 4.32it/s]\n 57%|█████▋ | 27/47 [00:06<00:04, 4.31it/s]\n 60%|█████▉ | 28/47 [00:06<00:04, 4.31it/s]\n 62%|██████▏ | 29/47 [00:06<00:04, 4.31it/s]\n 64%|██████▍ | 30/47 [00:06<00:03, 4.31it/s]\n 66%|██████▌ | 31/47 [00:07<00:03, 4.31it/s]\n 68%|██████▊ | 32/47 [00:07<00:03, 4.31it/s]\n 70%|███████ | 33/47 [00:07<00:03, 4.31it/s]\n 72%|███████▏ | 34/47 [00:07<00:03, 4.31it/s]\n 74%|███████▍ | 35/47 [00:08<00:02, 4.31it/s]\n 77%|███████▋ | 36/47 [00:08<00:02, 4.31it/s]\n 79%|███████▊ | 37/47 [00:08<00:02, 4.31it/s]\n 81%|████████ | 38/47 [00:08<00:02, 4.31it/s]\n 83%|████████▎ | 39/47 [00:09<00:01, 4.31it/s]\n 85%|████████▌ | 40/47 [00:09<00:01, 4.31it/s]\n 87%|████████▋ | 41/47 [00:09<00:01, 4.31it/s]\n 89%|████████▉ | 42/47 [00:09<00:01, 4.30it/s]\n 91%|█████████▏| 43/47 [00:09<00:00, 4.30it/s]\n 94%|█████████▎| 44/47 [00:10<00:00, 4.30it/s]\n 96%|█████████▌| 45/47 [00:10<00:00, 4.30it/s]\n 98%|█████████▊| 46/47 [00:10<00:00, 4.30it/s]\n100%|██████████| 47/47 [00:10<00:00, 4.30it/s]\n100%|██████████| 47/47 [00:10<00:00, 4.32it/s]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:00, 5.60it/s]\n 67%|██████▋ | 2/3 [00:00<00:00, 5.56it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.56it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.56it/s]", "metrics": { "predict_time": 13.143767, "total_time": 13.149376 }, "output": [ "https://replicate.delivery/pbxt/CGxE1DgG675SMNPUH8NAuTdHkEh3Cw3l78ze4XbR52f1wWeiA/out-0.png" ], "started_at": "2023-08-27T21:03:37.269792Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3orytllbjdnb36rlgrbfhmj4de", "cancel": "https://api.replicate.com/v1/predictions/3orytllbjdnb36rlgrbfhmj4de/cancel" }, "version": "45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f" }
Generated inUsing seed: 14896 Prompt: A photo in the style of <s0><s1>, interior, house - sustainable, minimalist, organic, light-filled, dynamic, efficient, autonomous, connected, harmonious, innovative, detailed, 8k, high resolution, sharp focus txt2img mode 0%| | 0/47 [00:00<?, ?it/s] 2%|▏ | 1/47 [00:00<00:10, 4.35it/s] 4%|▍ | 2/47 [00:00<00:10, 4.34it/s] 6%|▋ | 3/47 [00:00<00:10, 4.34it/s] 9%|▊ | 4/47 [00:00<00:09, 4.34it/s] 11%|█ | 5/47 [00:01<00:09, 4.33it/s] 13%|█▎ | 6/47 [00:01<00:09, 4.33it/s] 15%|█▍ | 7/47 [00:01<00:09, 4.33it/s] 17%|█▋ | 8/47 [00:01<00:09, 4.33it/s] 19%|█▉ | 9/47 [00:02<00:08, 4.33it/s] 21%|██▏ | 10/47 [00:02<00:08, 4.33it/s] 23%|██▎ | 11/47 [00:02<00:08, 4.32it/s] 26%|██▌ | 12/47 [00:02<00:08, 4.33it/s] 28%|██▊ | 13/47 [00:03<00:07, 4.32it/s] 30%|██▉ | 14/47 [00:03<00:07, 4.32it/s] 32%|███▏ | 15/47 [00:03<00:07, 4.32it/s] 34%|███▍ | 16/47 [00:03<00:07, 4.33it/s] 36%|███▌ | 17/47 [00:03<00:06, 4.33it/s] 38%|███▊ | 18/47 [00:04<00:06, 4.32it/s] 40%|████ | 19/47 [00:04<00:06, 4.32it/s] 43%|████▎ | 20/47 [00:04<00:06, 4.32it/s] 45%|████▍ | 21/47 [00:04<00:06, 4.32it/s] 47%|████▋ | 22/47 [00:05<00:05, 4.32it/s] 49%|████▉ | 23/47 [00:05<00:05, 4.32it/s] 51%|█████ | 24/47 [00:05<00:05, 4.32it/s] 53%|█████▎ | 25/47 [00:05<00:05, 4.31it/s] 55%|█████▌ | 26/47 [00:06<00:04, 4.32it/s] 57%|█████▋ | 27/47 [00:06<00:04, 4.31it/s] 60%|█████▉ | 28/47 [00:06<00:04, 4.31it/s] 62%|██████▏ | 29/47 [00:06<00:04, 4.31it/s] 64%|██████▍ | 30/47 [00:06<00:03, 4.31it/s] 66%|██████▌ | 31/47 [00:07<00:03, 4.31it/s] 68%|██████▊ | 32/47 [00:07<00:03, 4.31it/s] 70%|███████ | 33/47 [00:07<00:03, 4.31it/s] 72%|███████▏ | 34/47 [00:07<00:03, 4.31it/s] 74%|███████▍ | 35/47 [00:08<00:02, 4.31it/s] 77%|███████▋ | 36/47 [00:08<00:02, 4.31it/s] 79%|███████▊ | 37/47 [00:08<00:02, 4.31it/s] 81%|████████ | 38/47 [00:08<00:02, 4.31it/s] 83%|████████▎ | 39/47 [00:09<00:01, 4.31it/s] 85%|████████▌ | 40/47 [00:09<00:01, 4.31it/s] 87%|████████▋ | 41/47 [00:09<00:01, 4.31it/s] 89%|████████▉ | 42/47 [00:09<00:01, 4.30it/s] 91%|█████████▏| 43/47 [00:09<00:00, 4.30it/s] 94%|█████████▎| 44/47 [00:10<00:00, 4.30it/s] 96%|█████████▌| 45/47 [00:10<00:00, 4.30it/s] 98%|█████████▊| 46/47 [00:10<00:00, 4.30it/s] 100%|██████████| 47/47 [00:10<00:00, 4.30it/s] 100%|██████████| 47/47 [00:10<00:00, 4.32it/s] 0%| | 0/3 [00:00<?, ?it/s] 33%|███▎ | 1/3 [00:00<00:00, 5.60it/s] 67%|██████▋ | 2/3 [00:00<00:00, 5.56it/s] 100%|██████████| 3/3 [00:00<00:00, 5.56it/s] 100%|██████████| 3/3 [00:00<00:00, 5.56it/s]
Prediction
fofr/sdxl-tng-interior:45f1d0cfIDsschw4dbgcsehpay23hdtkp24qStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1152
- height
- 768
- prompt
- Am unreal engine render in the style of TOK, a bedroom on a spaceship
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.85
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.95
- negative_prompt
- low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a bedroom on a spaceship", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.85, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/sdxl-tng-interior using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-tng-interior:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", { input: { width: 1152, height: 768, prompt: "Am unreal engine render in the style of TOK, a bedroom on a spaceship", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.85, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.95, negative_prompt: "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run fofr/sdxl-tng-interior using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-tng-interior:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", input={ "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a bedroom on a spaceship", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.85, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/sdxl-tng-interior 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": "45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", "input": { "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a bedroom on a spaceship", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.85, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run fofr/sdxl-tng-interior using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/fofr/sdxl-tng-interior@sha256:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f \ -i 'width=1152' \ -i 'height=768' \ -i 'prompt="Am unreal engine render in the style of TOK, a bedroom on a spaceship"' \ -i 'refine="expert_ensemble_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.85' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=false' \ -i 'high_noise_frac=0.95' \ -i 'negative_prompt="low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Pull and run fofr/sdxl-tng-interior using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/fofr/sdxl-tng-interior@sha256:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a bedroom on a spaceship", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.85, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2023-08-27T21:13:50.776088Z", "created_at": "2023-08-27T21:13:28.887162Z", "data_removed": false, "error": null, "id": "sschw4dbgcsehpay23hdtkp24q", "input": { "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a bedroom on a spaceship", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.85, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 1793\nPrompt: Am unreal engine render in the style of <s0><s1>, a bedroom on a spaceship\ntxt2img mode\n 0%| | 0/47 [00:00<?, ?it/s]\n 2%|▏ | 1/47 [00:00<00:11, 4.10it/s]\n 4%|▍ | 2/47 [00:00<00:10, 4.20it/s]\n 6%|▋ | 3/47 [00:00<00:10, 4.23it/s]\n 9%|▊ | 4/47 [00:00<00:10, 4.25it/s]\n 11%|█ | 5/47 [00:01<00:09, 4.26it/s]\n 13%|█▎ | 6/47 [00:01<00:09, 4.26it/s]\n 15%|█▍ | 7/47 [00:01<00:09, 4.27it/s]\n 17%|█▋ | 8/47 [00:01<00:09, 4.27it/s]\n 19%|█▉ | 9/47 [00:02<00:08, 4.27it/s]\n 21%|██▏ | 10/47 [00:02<00:08, 4.27it/s]\n 23%|██▎ | 11/47 [00:02<00:08, 4.27it/s]\n 26%|██▌ | 12/47 [00:02<00:08, 4.27it/s]\n 28%|██▊ | 13/47 [00:03<00:07, 4.26it/s]\n 30%|██▉ | 14/47 [00:03<00:07, 4.27it/s]\n 32%|███▏ | 15/47 [00:03<00:07, 4.27it/s]\n 34%|███▍ | 16/47 [00:03<00:07, 4.27it/s]\n 36%|███▌ | 17/47 [00:03<00:07, 4.26it/s]\n 38%|███▊ | 18/47 [00:04<00:06, 4.27it/s]\n 40%|████ | 19/47 [00:04<00:06, 4.27it/s]\n 43%|████▎ | 20/47 [00:04<00:06, 4.26it/s]\n 45%|████▍ | 21/47 [00:04<00:06, 4.26it/s]\n 47%|████▋ | 22/47 [00:05<00:05, 4.27it/s]\n 49%|████▉ | 23/47 [00:05<00:05, 4.27it/s]\n 51%|█████ | 24/47 [00:05<00:05, 4.26it/s]\n 53%|█████▎ | 25/47 [00:05<00:05, 4.27it/s]\n 55%|█████▌ | 26/47 [00:06<00:04, 4.27it/s]\n 57%|█████▋ | 27/47 [00:06<00:04, 4.26it/s]\n 60%|█████▉ | 28/47 [00:06<00:04, 4.26it/s]\n 62%|██████▏ | 29/47 [00:06<00:04, 4.26it/s]\n 64%|██████▍ | 30/47 [00:07<00:03, 4.26it/s]\n 66%|██████▌ | 31/47 [00:07<00:03, 4.26it/s]\n 68%|██████▊ | 32/47 [00:07<00:03, 4.26it/s]\n 70%|███████ | 33/47 [00:07<00:03, 4.26it/s]\n 72%|███████▏ | 34/47 [00:07<00:03, 4.26it/s]\n 74%|███████▍ | 35/47 [00:08<00:02, 4.26it/s]\n 77%|███████▋ | 36/47 [00:08<00:02, 4.26it/s]\n 79%|███████▊ | 37/47 [00:08<00:02, 4.26it/s]\n 81%|████████ | 38/47 [00:08<00:02, 4.26it/s]\n 83%|████████▎ | 39/47 [00:09<00:01, 4.26it/s]\n 85%|████████▌ | 40/47 [00:09<00:01, 4.26it/s]\n 87%|████████▋ | 41/47 [00:09<00:01, 4.26it/s]\n 89%|████████▉ | 42/47 [00:09<00:01, 4.26it/s]\n 91%|█████████▏| 43/47 [00:10<00:00, 4.26it/s]\n 94%|█████████▎| 44/47 [00:10<00:00, 4.26it/s]\n 96%|█████████▌| 45/47 [00:10<00:00, 4.26it/s]\n 98%|█████████▊| 46/47 [00:10<00:00, 4.26it/s]\n100%|██████████| 47/47 [00:11<00:00, 4.26it/s]\n100%|██████████| 47/47 [00:11<00:00, 4.26it/s]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:00, 5.29it/s]\n 67%|██████▋ | 2/3 [00:00<00:00, 5.39it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.43it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.41it/s]", "metrics": { "predict_time": 13.282601, "total_time": 21.888926 }, "output": [ "https://replicate.delivery/pbxt/sYznwg7Zp0YzLxyVohFehXv5f5MgFxaLjJHpcrYo0hxN6WeiA/out-0.png" ], "started_at": "2023-08-27T21:13:37.493487Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/sschw4dbgcsehpay23hdtkp24q", "cancel": "https://api.replicate.com/v1/predictions/sschw4dbgcsehpay23hdtkp24q/cancel" }, "version": "45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f" }
Generated inUsing seed: 1793 Prompt: Am unreal engine render in the style of <s0><s1>, a bedroom on a spaceship txt2img mode 0%| | 0/47 [00:00<?, ?it/s] 2%|▏ | 1/47 [00:00<00:11, 4.10it/s] 4%|▍ | 2/47 [00:00<00:10, 4.20it/s] 6%|▋ | 3/47 [00:00<00:10, 4.23it/s] 9%|▊ | 4/47 [00:00<00:10, 4.25it/s] 11%|█ | 5/47 [00:01<00:09, 4.26it/s] 13%|█▎ | 6/47 [00:01<00:09, 4.26it/s] 15%|█▍ | 7/47 [00:01<00:09, 4.27it/s] 17%|█▋ | 8/47 [00:01<00:09, 4.27it/s] 19%|█▉ | 9/47 [00:02<00:08, 4.27it/s] 21%|██▏ | 10/47 [00:02<00:08, 4.27it/s] 23%|██▎ | 11/47 [00:02<00:08, 4.27it/s] 26%|██▌ | 12/47 [00:02<00:08, 4.27it/s] 28%|██▊ | 13/47 [00:03<00:07, 4.26it/s] 30%|██▉ | 14/47 [00:03<00:07, 4.27it/s] 32%|███▏ | 15/47 [00:03<00:07, 4.27it/s] 34%|███▍ | 16/47 [00:03<00:07, 4.27it/s] 36%|███▌ | 17/47 [00:03<00:07, 4.26it/s] 38%|███▊ | 18/47 [00:04<00:06, 4.27it/s] 40%|████ | 19/47 [00:04<00:06, 4.27it/s] 43%|████▎ | 20/47 [00:04<00:06, 4.26it/s] 45%|████▍ | 21/47 [00:04<00:06, 4.26it/s] 47%|████▋ | 22/47 [00:05<00:05, 4.27it/s] 49%|████▉ | 23/47 [00:05<00:05, 4.27it/s] 51%|█████ | 24/47 [00:05<00:05, 4.26it/s] 53%|█████▎ | 25/47 [00:05<00:05, 4.27it/s] 55%|█████▌ | 26/47 [00:06<00:04, 4.27it/s] 57%|█████▋ | 27/47 [00:06<00:04, 4.26it/s] 60%|█████▉ | 28/47 [00:06<00:04, 4.26it/s] 62%|██████▏ | 29/47 [00:06<00:04, 4.26it/s] 64%|██████▍ | 30/47 [00:07<00:03, 4.26it/s] 66%|██████▌ | 31/47 [00:07<00:03, 4.26it/s] 68%|██████▊ | 32/47 [00:07<00:03, 4.26it/s] 70%|███████ | 33/47 [00:07<00:03, 4.26it/s] 72%|███████▏ | 34/47 [00:07<00:03, 4.26it/s] 74%|███████▍ | 35/47 [00:08<00:02, 4.26it/s] 77%|███████▋ | 36/47 [00:08<00:02, 4.26it/s] 79%|███████▊ | 37/47 [00:08<00:02, 4.26it/s] 81%|████████ | 38/47 [00:08<00:02, 4.26it/s] 83%|████████▎ | 39/47 [00:09<00:01, 4.26it/s] 85%|████████▌ | 40/47 [00:09<00:01, 4.26it/s] 87%|████████▋ | 41/47 [00:09<00:01, 4.26it/s] 89%|████████▉ | 42/47 [00:09<00:01, 4.26it/s] 91%|█████████▏| 43/47 [00:10<00:00, 4.26it/s] 94%|█████████▎| 44/47 [00:10<00:00, 4.26it/s] 96%|█████████▌| 45/47 [00:10<00:00, 4.26it/s] 98%|█████████▊| 46/47 [00:10<00:00, 4.26it/s] 100%|██████████| 47/47 [00:11<00:00, 4.26it/s] 100%|██████████| 47/47 [00:11<00:00, 4.26it/s] 0%| | 0/3 [00:00<?, ?it/s] 33%|███▎ | 1/3 [00:00<00:00, 5.29it/s] 67%|██████▋ | 2/3 [00:00<00:00, 5.39it/s] 100%|██████████| 3/3 [00:00<00:00, 5.43it/s] 100%|██████████| 3/3 [00:00<00:00, 5.41it/s]
Prediction
fofr/sdxl-tng-interior:45f1d0cfIDatsdwwlb7c7dlvnn5tkwecbenaStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1152
- height
- 768
- prompt
- Am unreal engine render in the style of TOK, a portrait of a woman, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.9
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.95
- negative_prompt
- low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a portrait of a woman, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/sdxl-tng-interior using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-tng-interior:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", { input: { width: 1152, height: 768, prompt: "Am unreal engine render in the style of TOK, a portrait of a woman, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.9, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.95, negative_prompt: "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run fofr/sdxl-tng-interior using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-tng-interior:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", input={ "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a portrait of a woman, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/sdxl-tng-interior 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": "45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", "input": { "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a portrait of a woman, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run fofr/sdxl-tng-interior using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/fofr/sdxl-tng-interior@sha256:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f \ -i 'width=1152' \ -i 'height=768' \ -i 'prompt="Am unreal engine render in the style of TOK, a portrait of a woman, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks"' \ -i 'refine="expert_ensemble_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.9' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=false' \ -i 'high_noise_frac=0.95' \ -i 'negative_prompt="low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Pull and run fofr/sdxl-tng-interior using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/fofr/sdxl-tng-interior@sha256:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a portrait of a woman, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2023-08-27T21:22:16.168203Z", "created_at": "2023-08-27T21:22:03.516880Z", "data_removed": false, "error": null, "id": "atsdwwlb7c7dlvnn5tkwecbena", "input": { "width": 1152, "height": 768, "prompt": "Am unreal engine render in the style of TOK, a portrait of a woman, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 27696\nPrompt: Am unreal engine render in the style of <s0><s1>, a portrait of a woman, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks\ntxt2img mode\n 0%| | 0/47 [00:00<?, ?it/s]\n 2%|▏ | 1/47 [00:00<00:11, 4.14it/s]\n 4%|▍ | 2/47 [00:00<00:10, 4.24it/s]\n 6%|▋ | 3/47 [00:00<00:10, 4.26it/s]\n 9%|▊ | 4/47 [00:00<00:10, 4.27it/s]\n 11%|█ | 5/47 [00:01<00:09, 4.28it/s]\n 13%|█▎ | 6/47 [00:01<00:09, 4.28it/s]\n 15%|█▍ | 7/47 [00:01<00:09, 4.29it/s]\n 17%|█▋ | 8/47 [00:01<00:09, 4.29it/s]\n 19%|█▉ | 9/47 [00:02<00:08, 4.29it/s]\n 21%|██▏ | 10/47 [00:02<00:08, 4.29it/s]\n 23%|██▎ | 11/47 [00:02<00:08, 4.29it/s]\n 26%|██▌ | 12/47 [00:02<00:08, 4.29it/s]\n 28%|██▊ | 13/47 [00:03<00:07, 4.29it/s]\n 30%|██▉ | 14/47 [00:03<00:07, 4.29it/s]\n 32%|███▏ | 15/47 [00:03<00:07, 4.28it/s]\n 34%|███▍ | 16/47 [00:03<00:07, 4.28it/s]\n 36%|███▌ | 17/47 [00:03<00:07, 4.28it/s]\n 38%|███▊ | 18/47 [00:04<00:06, 4.28it/s]\n 40%|████ | 19/47 [00:04<00:06, 4.28it/s]\n 43%|████▎ | 20/47 [00:04<00:06, 4.28it/s]\n 45%|████▍ | 21/47 [00:04<00:06, 4.28it/s]\n 47%|████▋ | 22/47 [00:05<00:05, 4.28it/s]\n 49%|████▉ | 23/47 [00:05<00:05, 4.28it/s]\n 51%|█████ | 24/47 [00:05<00:05, 4.28it/s]\n 53%|█████▎ | 25/47 [00:05<00:05, 4.28it/s]\n 55%|█████▌ | 26/47 [00:06<00:04, 4.28it/s]\n 57%|█████▋ | 27/47 [00:06<00:04, 4.28it/s]\n 60%|█████▉ | 28/47 [00:06<00:04, 4.27it/s]\n 62%|██████▏ | 29/47 [00:06<00:04, 4.27it/s]\n 64%|██████▍ | 30/47 [00:07<00:03, 4.27it/s]\n 66%|██████▌ | 31/47 [00:07<00:03, 4.27it/s]\n 68%|██████▊ | 32/47 [00:07<00:03, 4.27it/s]\n 70%|███████ | 33/47 [00:07<00:03, 4.28it/s]\n 72%|███████▏ | 34/47 [00:07<00:03, 4.27it/s]\n 74%|███████▍ | 35/47 [00:08<00:02, 4.27it/s]\n 77%|███████▋ | 36/47 [00:08<00:02, 4.27it/s]\n 79%|███████▊ | 37/47 [00:08<00:02, 4.27it/s]\n 81%|████████ | 38/47 [00:08<00:02, 4.27it/s]\n 83%|████████▎ | 39/47 [00:09<00:01, 4.27it/s]\n 85%|████████▌ | 40/47 [00:09<00:01, 4.27it/s]\n 87%|████████▋ | 41/47 [00:09<00:01, 4.27it/s]\n 89%|████████▉ | 42/47 [00:09<00:01, 4.27it/s]\n 91%|█████████▏| 43/47 [00:10<00:00, 4.27it/s]\n 94%|█████████▎| 44/47 [00:10<00:00, 4.27it/s]\n 96%|█████████▌| 45/47 [00:10<00:00, 4.27it/s]\n 98%|█████████▊| 46/47 [00:10<00:00, 4.27it/s]\n100%|██████████| 47/47 [00:10<00:00, 4.27it/s]\n100%|██████████| 47/47 [00:10<00:00, 4.28it/s]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:00, 5.28it/s]\n 67%|██████▋ | 2/3 [00:00<00:00, 5.40it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.44it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.41it/s]", "metrics": { "predict_time": 12.679061, "total_time": 12.651323 }, "output": [ "https://replicate.delivery/pbxt/P9XQrfKwbtxrJyfcj68otlUP9Bxk2nWWZLPZnTdU4FjHCXeiA/out-0.png" ], "started_at": "2023-08-27T21:22:03.489142Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/atsdwwlb7c7dlvnn5tkwecbena", "cancel": "https://api.replicate.com/v1/predictions/atsdwwlb7c7dlvnn5tkwecbena/cancel" }, "version": "45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f" }
Generated inUsing seed: 27696 Prompt: Am unreal engine render in the style of <s0><s1>, a portrait of a woman, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks txt2img mode 0%| | 0/47 [00:00<?, ?it/s] 2%|▏ | 1/47 [00:00<00:11, 4.14it/s] 4%|▍ | 2/47 [00:00<00:10, 4.24it/s] 6%|▋ | 3/47 [00:00<00:10, 4.26it/s] 9%|▊ | 4/47 [00:00<00:10, 4.27it/s] 11%|█ | 5/47 [00:01<00:09, 4.28it/s] 13%|█▎ | 6/47 [00:01<00:09, 4.28it/s] 15%|█▍ | 7/47 [00:01<00:09, 4.29it/s] 17%|█▋ | 8/47 [00:01<00:09, 4.29it/s] 19%|█▉ | 9/47 [00:02<00:08, 4.29it/s] 21%|██▏ | 10/47 [00:02<00:08, 4.29it/s] 23%|██▎ | 11/47 [00:02<00:08, 4.29it/s] 26%|██▌ | 12/47 [00:02<00:08, 4.29it/s] 28%|██▊ | 13/47 [00:03<00:07, 4.29it/s] 30%|██▉ | 14/47 [00:03<00:07, 4.29it/s] 32%|███▏ | 15/47 [00:03<00:07, 4.28it/s] 34%|███▍ | 16/47 [00:03<00:07, 4.28it/s] 36%|███▌ | 17/47 [00:03<00:07, 4.28it/s] 38%|███▊ | 18/47 [00:04<00:06, 4.28it/s] 40%|████ | 19/47 [00:04<00:06, 4.28it/s] 43%|████▎ | 20/47 [00:04<00:06, 4.28it/s] 45%|████▍ | 21/47 [00:04<00:06, 4.28it/s] 47%|████▋ | 22/47 [00:05<00:05, 4.28it/s] 49%|████▉ | 23/47 [00:05<00:05, 4.28it/s] 51%|█████ | 24/47 [00:05<00:05, 4.28it/s] 53%|█████▎ | 25/47 [00:05<00:05, 4.28it/s] 55%|█████▌ | 26/47 [00:06<00:04, 4.28it/s] 57%|█████▋ | 27/47 [00:06<00:04, 4.28it/s] 60%|█████▉ | 28/47 [00:06<00:04, 4.27it/s] 62%|██████▏ | 29/47 [00:06<00:04, 4.27it/s] 64%|██████▍ | 30/47 [00:07<00:03, 4.27it/s] 66%|██████▌ | 31/47 [00:07<00:03, 4.27it/s] 68%|██████▊ | 32/47 [00:07<00:03, 4.27it/s] 70%|███████ | 33/47 [00:07<00:03, 4.28it/s] 72%|███████▏ | 34/47 [00:07<00:03, 4.27it/s] 74%|███████▍ | 35/47 [00:08<00:02, 4.27it/s] 77%|███████▋ | 36/47 [00:08<00:02, 4.27it/s] 79%|███████▊ | 37/47 [00:08<00:02, 4.27it/s] 81%|████████ | 38/47 [00:08<00:02, 4.27it/s] 83%|████████▎ | 39/47 [00:09<00:01, 4.27it/s] 85%|████████▌ | 40/47 [00:09<00:01, 4.27it/s] 87%|████████▋ | 41/47 [00:09<00:01, 4.27it/s] 89%|████████▉ | 42/47 [00:09<00:01, 4.27it/s] 91%|█████████▏| 43/47 [00:10<00:00, 4.27it/s] 94%|█████████▎| 44/47 [00:10<00:00, 4.27it/s] 96%|█████████▌| 45/47 [00:10<00:00, 4.27it/s] 98%|█████████▊| 46/47 [00:10<00:00, 4.27it/s] 100%|██████████| 47/47 [00:10<00:00, 4.27it/s] 100%|██████████| 47/47 [00:10<00:00, 4.28it/s] 0%| | 0/3 [00:00<?, ?it/s] 33%|███▎ | 1/3 [00:00<00:00, 5.28it/s] 67%|██████▋ | 2/3 [00:00<00:00, 5.40it/s] 100%|██████████| 3/3 [00:00<00:00, 5.44it/s] 100%|██████████| 3/3 [00:00<00:00, 5.41it/s]
Prediction
fofr/sdxl-tng-interior:45f1d0cfIDox7gvldb435pir4mfwgowyav2uStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1152
- height
- 768
- prompt
- An unreal engine render in the style of TOK, a close-up portrait of a black woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.9
- num_outputs
- 4
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.95
- negative_prompt
- low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1152, "height": 768, "prompt": "An unreal engine render in the style of TOK, a close-up portrait of a black woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 }
npm install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the clientimport Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run fofr/sdxl-tng-interior using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-tng-interior:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", { input: { width: 1152, height: 768, prompt: "An unreal engine render in the style of TOK, a close-up portrait of a black woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.9, num_outputs: 4, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.95, negative_prompt: "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the clientimport replicate
Run fofr/sdxl-tng-interior using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-tng-interior:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", input={ "width": 1152, "height": 768, "prompt": "An unreal engine render in the style of TOK, a close-up portrait of a black woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run fofr/sdxl-tng-interior 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": "45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f", "input": { "width": 1152, "height": 768, "prompt": "An unreal engine render in the style of TOK, a close-up portrait of a black woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Install Cogbrew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run fofr/sdxl-tng-interior using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/fofr/sdxl-tng-interior@sha256:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f \ -i 'width=1152' \ -i 'height=768' \ -i 'prompt="An unreal engine render in the style of TOK, a close-up portrait of a black woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks"' \ -i 'refine="expert_ensemble_refiner"' \ -i 'scheduler="K_EULER"' \ -i 'lora_scale=0.9' \ -i 'num_outputs=4' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=false' \ -i 'high_noise_frac=0.95' \ -i 'negative_prompt="low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Pull and run fofr/sdxl-tng-interior using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/fofr/sdxl-tng-interior@sha256:45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1152, "height": 768, "prompt": "An unreal engine render in the style of TOK, a close-up portrait of a black woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
Output
{ "completed_at": "2023-08-27T21:31:34.588407Z", "created_at": "2023-08-27T21:30:40.371737Z", "data_removed": false, "error": null, "id": "ox7gvldb435pir4mfwgowyav2u", "input": { "width": 1152, "height": 768, "prompt": "An unreal engine render in the style of TOK, a close-up portrait of a black woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.9, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "low resolution, blurred, soft, jpeg artefacts, broken, distorted, ugly, disfigured", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 39138\nPrompt: An unreal engine render in the style of <s0><s1>, a close-up portrait of a black woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks\ntxt2img mode\n 0%| | 0/47 [00:00<?, ?it/s]\n 2%|▏ | 1/47 [00:00<00:38, 1.18it/s]\n 4%|▍ | 2/47 [00:01<00:38, 1.18it/s]\n 6%|▋ | 3/47 [00:02<00:37, 1.18it/s]\n 9%|▊ | 4/47 [00:03<00:36, 1.18it/s]\n 11%|█ | 5/47 [00:04<00:35, 1.17it/s]\n 13%|█▎ | 6/47 [00:05<00:34, 1.17it/s]\n 15%|█▍ | 7/47 [00:05<00:34, 1.17it/s]\n 17%|█▋ | 8/47 [00:06<00:33, 1.17it/s]\n 19%|█▉ | 9/47 [00:07<00:32, 1.17it/s]\n 21%|██▏ | 10/47 [00:08<00:31, 1.17it/s]\n 23%|██▎ | 11/47 [00:09<00:30, 1.17it/s]\n 26%|██▌ | 12/47 [00:10<00:29, 1.17it/s]\n 28%|██▊ | 13/47 [00:11<00:29, 1.17it/s]\n 30%|██▉ | 14/47 [00:11<00:28, 1.17it/s]\n 32%|███▏ | 15/47 [00:12<00:27, 1.17it/s]\n 34%|███▍ | 16/47 [00:13<00:26, 1.17it/s]\n 36%|███▌ | 17/47 [00:14<00:25, 1.17it/s]\n 38%|███▊ | 18/47 [00:15<00:24, 1.17it/s]\n 40%|████ | 19/47 [00:16<00:23, 1.17it/s]\n 43%|████▎ | 20/47 [00:17<00:23, 1.17it/s]\n 45%|████▍ | 21/47 [00:17<00:22, 1.17it/s]\n 47%|████▋ | 22/47 [00:18<00:21, 1.17it/s]\n 49%|████▉ | 23/47 [00:19<00:20, 1.17it/s]\n 51%|█████ | 24/47 [00:20<00:19, 1.17it/s]\n 53%|█████▎ | 25/47 [00:21<00:18, 1.17it/s]\n 55%|█████▌ | 26/47 [00:22<00:17, 1.17it/s]\n 57%|█████▋ | 27/47 [00:23<00:17, 1.16it/s]\n 60%|█████▉ | 28/47 [00:23<00:16, 1.17it/s]\n 62%|██████▏ | 29/47 [00:24<00:15, 1.17it/s]\n 64%|██████▍ | 30/47 [00:25<00:14, 1.17it/s]\n 66%|██████▌ | 31/47 [00:26<00:13, 1.17it/s]\n 68%|██████▊ | 32/47 [00:27<00:12, 1.17it/s]\n 70%|███████ | 33/47 [00:28<00:11, 1.17it/s]\n 72%|███████▏ | 34/47 [00:29<00:11, 1.17it/s]\n 74%|███████▍ | 35/47 [00:29<00:10, 1.17it/s]\n 77%|███████▋ | 36/47 [00:30<00:09, 1.17it/s]\n 79%|███████▊ | 37/47 [00:31<00:08, 1.17it/s]\n 81%|████████ | 38/47 [00:32<00:07, 1.17it/s]\n 83%|████████▎ | 39/47 [00:33<00:06, 1.17it/s]\n 85%|████████▌ | 40/47 [00:34<00:05, 1.17it/s]\n 87%|████████▋ | 41/47 [00:35<00:05, 1.17it/s]\n 89%|████████▉ | 42/47 [00:35<00:04, 1.17it/s]\n 91%|█████████▏| 43/47 [00:36<00:03, 1.17it/s]\n 94%|█████████▎| 44/47 [00:37<00:02, 1.17it/s]\n 96%|█████████▌| 45/47 [00:38<00:01, 1.17it/s]\n 98%|█████████▊| 46/47 [00:39<00:00, 1.17it/s]\n100%|██████████| 47/47 [00:40<00:00, 1.17it/s]\n100%|██████████| 47/47 [00:40<00:00, 1.17it/s]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:01, 1.50it/s]\n 67%|██████▋ | 2/3 [00:01<00:00, 1.49it/s]\n100%|██████████| 3/3 [00:02<00:00, 1.49it/s]\n100%|██████████| 3/3 [00:02<00:00, 1.49it/s]", "metrics": { "predict_time": 45.916954, "total_time": 54.21667 }, "output": [ "https://replicate.delivery/pbxt/PZff9HzDIqjftpyfO4fwa9JwEFgyEifcOhvaYPQzQHKealLvIA/out-0.png", "https://replicate.delivery/pbxt/mOrm6ulsAApFMxyZYUjrsv2JXxSZpufUhpB72xueTF61KXeiA/out-1.png", "https://replicate.delivery/pbxt/snAzqTAfrP0XAazBSc87127QPh1jGfHxSsGohd6TfMMsVu8iA/out-2.png", "https://replicate.delivery/pbxt/2v3MBDoJyOqBMdzQdjqwkVct87eWXDAQcYOfgI9jkhm2KXeiA/out-3.png" ], "started_at": "2023-08-27T21:30:48.671453Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ox7gvldb435pir4mfwgowyav2u", "cancel": "https://api.replicate.com/v1/predictions/ox7gvldb435pir4mfwgowyav2u/cancel" }, "version": "45f1d0cf3445f54d4b19a2a03e53b15abd7237ea72e2fb4824b193ffa429e31f" }
Generated inUsing seed: 39138 Prompt: An unreal engine render in the style of <s0><s1>, a close-up portrait of a black woman in a living room, star trek uniform, detailed, high resolution, dynamic, action, bokeh, sparks txt2img mode 0%| | 0/47 [00:00<?, ?it/s] 2%|▏ | 1/47 [00:00<00:38, 1.18it/s] 4%|▍ | 2/47 [00:01<00:38, 1.18it/s] 6%|▋ | 3/47 [00:02<00:37, 1.18it/s] 9%|▊ | 4/47 [00:03<00:36, 1.18it/s] 11%|█ | 5/47 [00:04<00:35, 1.17it/s] 13%|█▎ | 6/47 [00:05<00:34, 1.17it/s] 15%|█▍ | 7/47 [00:05<00:34, 1.17it/s] 17%|█▋ | 8/47 [00:06<00:33, 1.17it/s] 19%|█▉ | 9/47 [00:07<00:32, 1.17it/s] 21%|██▏ | 10/47 [00:08<00:31, 1.17it/s] 23%|██▎ | 11/47 [00:09<00:30, 1.17it/s] 26%|██▌ | 12/47 [00:10<00:29, 1.17it/s] 28%|██▊ | 13/47 [00:11<00:29, 1.17it/s] 30%|██▉ | 14/47 [00:11<00:28, 1.17it/s] 32%|███▏ | 15/47 [00:12<00:27, 1.17it/s] 34%|███▍ | 16/47 [00:13<00:26, 1.17it/s] 36%|███▌ | 17/47 [00:14<00:25, 1.17it/s] 38%|███▊ | 18/47 [00:15<00:24, 1.17it/s] 40%|████ | 19/47 [00:16<00:23, 1.17it/s] 43%|████▎ | 20/47 [00:17<00:23, 1.17it/s] 45%|████▍ | 21/47 [00:17<00:22, 1.17it/s] 47%|████▋ | 22/47 [00:18<00:21, 1.17it/s] 49%|████▉ | 23/47 [00:19<00:20, 1.17it/s] 51%|█████ | 24/47 [00:20<00:19, 1.17it/s] 53%|█████▎ | 25/47 [00:21<00:18, 1.17it/s] 55%|█████▌ | 26/47 [00:22<00:17, 1.17it/s] 57%|█████▋ | 27/47 [00:23<00:17, 1.16it/s] 60%|█████▉ | 28/47 [00:23<00:16, 1.17it/s] 62%|██████▏ | 29/47 [00:24<00:15, 1.17it/s] 64%|██████▍ | 30/47 [00:25<00:14, 1.17it/s] 66%|██████▌ | 31/47 [00:26<00:13, 1.17it/s] 68%|██████▊ | 32/47 [00:27<00:12, 1.17it/s] 70%|███████ | 33/47 [00:28<00:11, 1.17it/s] 72%|███████▏ | 34/47 [00:29<00:11, 1.17it/s] 74%|███████▍ | 35/47 [00:29<00:10, 1.17it/s] 77%|███████▋ | 36/47 [00:30<00:09, 1.17it/s] 79%|███████▊ | 37/47 [00:31<00:08, 1.17it/s] 81%|████████ | 38/47 [00:32<00:07, 1.17it/s] 83%|████████▎ | 39/47 [00:33<00:06, 1.17it/s] 85%|████████▌ | 40/47 [00:34<00:05, 1.17it/s] 87%|████████▋ | 41/47 [00:35<00:05, 1.17it/s] 89%|████████▉ | 42/47 [00:35<00:04, 1.17it/s] 91%|█████████▏| 43/47 [00:36<00:03, 1.17it/s] 94%|█████████▎| 44/47 [00:37<00:02, 1.17it/s] 96%|█████████▌| 45/47 [00:38<00:01, 1.17it/s] 98%|█████████▊| 46/47 [00:39<00:00, 1.17it/s] 100%|██████████| 47/47 [00:40<00:00, 1.17it/s] 100%|██████████| 47/47 [00:40<00:00, 1.17it/s] 0%| | 0/3 [00:00<?, ?it/s] 33%|███▎ | 1/3 [00:00<00:01, 1.50it/s] 67%|██████▋ | 2/3 [00:01<00:00, 1.49it/s] 100%|██████████| 3/3 [00:02<00:00, 1.49it/s] 100%|██████████| 3/3 [00:02<00:00, 1.49it/s]
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