datacte / proteus-v0.3
ProteusV0.3: The Anime Update
Prediction
datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48IDvx4zotdbs3bcllpxese2nqnpteStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- Anime full body portrait of a swordsman holding his weapon in front of him. He is facing the camera with a fierce look on his face. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)
- scheduler
- DPM++2MSDE
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- negative_prompt
- worst quality, low quality
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 1024, "height": 1024, "prompt": "Anime full body portrait of a swordsman holding his weapon in front of him. He is facing the camera with a fierce look on his face. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "worst quality, low quality", "prompt_strength": 0.8, "num_inference_steps": 30 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run datacte/proteus-v0.3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", { input: { width: 1024, height: 1024, prompt: "Anime full body portrait of a swordsman holding his weapon in front of him. He is facing the camera with a fierce look on his face. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)", scheduler: "DPM++2MSDE", num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, negative_prompt: "worst quality, low quality", prompt_strength: 0.8, num_inference_steps: 30 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run datacte/proteus-v0.3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", input={ "width": 1024, "height": 1024, "prompt": "Anime full body portrait of a swordsman holding his weapon in front of him. He is facing the camera with a fierce look on his face. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "negative_prompt": "worst quality, low quality", "prompt_strength": 0.8, "num_inference_steps": 30 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run datacte/proteus-v0.3 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": "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", "input": { "width": 1024, "height": 1024, "prompt": "Anime full body portrait of a swordsman holding his weapon in front of him. He is facing the camera with a fierce look on his face. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "worst quality, low quality", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/datacte/proteus-v0.3@sha256:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48 \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="Anime full body portrait of a swordsman holding his weapon in front of him. He is facing the camera with a fierce look on his face. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)"' \ -i 'scheduler="DPM++2MSDE"' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=true' \ -i 'negative_prompt="worst quality, low quality"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=30'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/datacte/proteus-v0.3@sha256:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "Anime full body portrait of a swordsman holding his weapon in front of him. He is facing the camera with a fierce look on his face. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "worst quality, low quality", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-02-14T20:05:46.002402Z", "created_at": "2024-02-14T20:03:34.936592Z", "data_removed": false, "error": null, "id": "vx4zotdbs3bcllpxese2nqnpte", "input": { "width": 1024, "height": 1024, "prompt": "Anime full body portrait of a swordsman holding his weapon in front of him. He is facing the camera with a fierce look on his face. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "worst quality, low quality", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 3937703446\nPrompt: Anime full body portrait of a swordsman holding his weapon in front of him. He is facing the camera with a fierce look on his face. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)\ntxt2img mode\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:14, 2.05it/s]\n 7%|▋ | 2/30 [00:00<00:12, 2.30it/s]\n 10%|█ | 3/30 [00:01<00:11, 2.38it/s]\n 13%|█▎ | 4/30 [00:01<00:10, 2.42it/s]\n 17%|█▋ | 5/30 [00:02<00:10, 2.45it/s]\n 20%|██ | 6/30 [00:02<00:09, 2.46it/s]\n 23%|██▎ | 7/30 [00:02<00:09, 2.46it/s]\n 27%|██▋ | 8/30 [00:03<00:08, 2.47it/s]\n 30%|███ | 9/30 [00:03<00:08, 2.47it/s]\n 33%|███▎ | 10/30 [00:04<00:08, 2.48it/s]\n 37%|███▋ | 11/30 [00:04<00:07, 2.48it/s]\n 40%|████ | 12/30 [00:04<00:07, 2.48it/s]\n 43%|████▎ | 13/30 [00:05<00:06, 2.48it/s]\n 47%|████▋ | 14/30 [00:05<00:06, 2.48it/s]\n 50%|█████ | 15/30 [00:06<00:06, 2.48it/s]\n 53%|█████▎ | 16/30 [00:06<00:05, 2.48it/s]\n 57%|█████▋ | 17/30 [00:06<00:05, 2.48it/s]\n 60%|██████ | 18/30 [00:07<00:04, 2.48it/s]\n 63%|██████▎ | 19/30 [00:07<00:04, 2.48it/s]\n 67%|██████▋ | 20/30 [00:08<00:04, 2.47it/s]\n 70%|███████ | 21/30 [00:08<00:03, 2.47it/s]\n 73%|███████▎ | 22/30 [00:08<00:03, 2.47it/s]\n 77%|███████▋ | 23/30 [00:09<00:02, 2.47it/s]\n 80%|████████ | 24/30 [00:09<00:02, 2.47it/s]\n 83%|████████▎ | 25/30 [00:10<00:02, 2.47it/s]\n 87%|████████▋ | 26/30 [00:10<00:01, 2.47it/s]\n 90%|█████████ | 27/30 [00:10<00:01, 2.47it/s]\n 93%|█████████▎| 28/30 [00:11<00:00, 2.47it/s]\n 97%|█████████▋| 29/30 [00:11<00:00, 2.47it/s]\n100%|██████████| 30/30 [00:11<00:00, 2.90it/s]\n100%|██████████| 30/30 [00:11<00:00, 2.50it/s]", "metrics": { "predict_time": 14.601853, "total_time": 131.06581 }, "output": [ "https://replicate.delivery/pbxt/YQA6VCqkKV5mAVN7O69zBQfAOtvxoIkSTFJ6dfDoMaaY8sWSA/out-0.png" ], "started_at": "2024-02-14T20:05:31.400549Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/vx4zotdbs3bcllpxese2nqnpte", "cancel": "https://api.replicate.com/v1/predictions/vx4zotdbs3bcllpxese2nqnpte/cancel" }, "version": "b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48" }
Generated inUsing seed: 3937703446 Prompt: Anime full body portrait of a swordsman holding his weapon in front of him. He is facing the camera with a fierce look on his face. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2) txt2img mode 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:14, 2.05it/s] 7%|▋ | 2/30 [00:00<00:12, 2.30it/s] 10%|█ | 3/30 [00:01<00:11, 2.38it/s] 13%|█▎ | 4/30 [00:01<00:10, 2.42it/s] 17%|█▋ | 5/30 [00:02<00:10, 2.45it/s] 20%|██ | 6/30 [00:02<00:09, 2.46it/s] 23%|██▎ | 7/30 [00:02<00:09, 2.46it/s] 27%|██▋ | 8/30 [00:03<00:08, 2.47it/s] 30%|███ | 9/30 [00:03<00:08, 2.47it/s] 33%|███▎ | 10/30 [00:04<00:08, 2.48it/s] 37%|███▋ | 11/30 [00:04<00:07, 2.48it/s] 40%|████ | 12/30 [00:04<00:07, 2.48it/s] 43%|████▎ | 13/30 [00:05<00:06, 2.48it/s] 47%|████▋ | 14/30 [00:05<00:06, 2.48it/s] 50%|█████ | 15/30 [00:06<00:06, 2.48it/s] 53%|█████▎ | 16/30 [00:06<00:05, 2.48it/s] 57%|█████▋ | 17/30 [00:06<00:05, 2.48it/s] 60%|██████ | 18/30 [00:07<00:04, 2.48it/s] 63%|██████▎ | 19/30 [00:07<00:04, 2.48it/s] 67%|██████▋ | 20/30 [00:08<00:04, 2.47it/s] 70%|███████ | 21/30 [00:08<00:03, 2.47it/s] 73%|███████▎ | 22/30 [00:08<00:03, 2.47it/s] 77%|███████▋ | 23/30 [00:09<00:02, 2.47it/s] 80%|████████ | 24/30 [00:09<00:02, 2.47it/s] 83%|████████▎ | 25/30 [00:10<00:02, 2.47it/s] 87%|████████▋ | 26/30 [00:10<00:01, 2.47it/s] 90%|█████████ | 27/30 [00:10<00:01, 2.47it/s] 93%|█████████▎| 28/30 [00:11<00:00, 2.47it/s] 97%|█████████▋| 29/30 [00:11<00:00, 2.47it/s] 100%|██████████| 30/30 [00:11<00:00, 2.90it/s] 100%|██████████| 30/30 [00:11<00:00, 2.50it/s]
Prediction
datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48IDaobq2r3b6m3fvdkaizg6jj77qeStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- spacious,circular underground room,{dirtied white tiles},amalgamation,flesh,plastic,dark fabric,core,pulsating heart,limbs,human-like arms,twisted angelic wings,arms,covered in skin,feathers,scales,undulate slowly,unseen current,convulsing,head area,chaotic,mass of eyes,mouths,no human features,smaller forms,cherubs,demons,golden wires,surround,holy light,tv static effect,golden glow,shadows,terrifying essence,overwhelming presence,nightmarish,landscape,sparse,cavernous,eerie,dynamic,motion,striking,awe-inspiring,nightmarish,nightmarish,nightmare,horrifying,bio-mechanical,body horror,amalgamation
- scheduler
- DPM++2MSDE
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- negative_prompt
- nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image
- prompt_strength
- 0.8
- num_inference_steps
- 20
{ "width": 1024, "height": 1024, "prompt": "spacious,circular underground room,{dirtied white tiles},amalgamation,flesh,plastic,dark fabric,core,pulsating heart,limbs,human-like arms,twisted angelic wings,arms,covered in skin,feathers,scales,undulate slowly,unseen current,convulsing,head area,chaotic,mass of eyes,mouths,no human features,smaller forms,cherubs,demons,golden wires,surround,holy light,tv static effect,golden glow,shadows,terrifying essence,overwhelming presence,nightmarish,landscape,sparse,cavernous,eerie,dynamic,motion,striking,awe-inspiring,nightmarish,nightmarish,nightmare,horrifying,bio-mechanical,body horror,amalgamation", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 20 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run datacte/proteus-v0.3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", { input: { width: 1024, height: 1024, prompt: "spacious,circular underground room,{dirtied white tiles},amalgamation,flesh,plastic,dark fabric,core,pulsating heart,limbs,human-like arms,twisted angelic wings,arms,covered in skin,feathers,scales,undulate slowly,unseen current,convulsing,head area,chaotic,mass of eyes,mouths,no human features,smaller forms,cherubs,demons,golden wires,surround,holy light,tv static effect,golden glow,shadows,terrifying essence,overwhelming presence,nightmarish,landscape,sparse,cavernous,eerie,dynamic,motion,striking,awe-inspiring,nightmarish,nightmarish,nightmare,horrifying,bio-mechanical,body horror,amalgamation", scheduler: "DPM++2MSDE", num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, negative_prompt: "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", prompt_strength: 0.8, num_inference_steps: 20 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run datacte/proteus-v0.3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", input={ "width": 1024, "height": 1024, "prompt": "spacious,circular underground room,{dirtied white tiles},amalgamation,flesh,plastic,dark fabric,core,pulsating heart,limbs,human-like arms,twisted angelic wings,arms,covered in skin,feathers,scales,undulate slowly,unseen current,convulsing,head area,chaotic,mass of eyes,mouths,no human features,smaller forms,cherubs,demons,golden wires,surround,holy light,tv static effect,golden glow,shadows,terrifying essence,overwhelming presence,nightmarish,landscape,sparse,cavernous,eerie,dynamic,motion,striking,awe-inspiring,nightmarish,nightmarish,nightmare,horrifying,bio-mechanical,body horror,amalgamation", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 20 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run datacte/proteus-v0.3 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": "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", "input": { "width": 1024, "height": 1024, "prompt": "spacious,circular underground room,{dirtied white tiles},amalgamation,flesh,plastic,dark fabric,core,pulsating heart,limbs,human-like arms,twisted angelic wings,arms,covered in skin,feathers,scales,undulate slowly,unseen current,convulsing,head area,chaotic,mass of eyes,mouths,no human features,smaller forms,cherubs,demons,golden wires,surround,holy light,tv static effect,golden glow,shadows,terrifying essence,overwhelming presence,nightmarish,landscape,sparse,cavernous,eerie,dynamic,motion,striking,awe-inspiring,nightmarish,nightmarish,nightmare,horrifying,bio-mechanical,body horror,amalgamation", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 20 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/datacte/proteus-v0.3@sha256:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48 \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="spacious,circular underground room,{dirtied white tiles},amalgamation,flesh,plastic,dark fabric,core,pulsating heart,limbs,human-like arms,twisted angelic wings,arms,covered in skin,feathers,scales,undulate slowly,unseen current,convulsing,head area,chaotic,mass of eyes,mouths,no human features,smaller forms,cherubs,demons,golden wires,surround,holy light,tv static effect,golden glow,shadows,terrifying essence,overwhelming presence,nightmarish,landscape,sparse,cavernous,eerie,dynamic,motion,striking,awe-inspiring,nightmarish,nightmarish,nightmare,horrifying,bio-mechanical,body horror,amalgamation"' \ -i 'scheduler="DPM++2MSDE"' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=true' \ -i 'negative_prompt="nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=20'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/datacte/proteus-v0.3@sha256:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "spacious,circular underground room,{dirtied white tiles},amalgamation,flesh,plastic,dark fabric,core,pulsating heart,limbs,human-like arms,twisted angelic wings,arms,covered in skin,feathers,scales,undulate slowly,unseen current,convulsing,head area,chaotic,mass of eyes,mouths,no human features,smaller forms,cherubs,demons,golden wires,surround,holy light,tv static effect,golden glow,shadows,terrifying essence,overwhelming presence,nightmarish,landscape,sparse,cavernous,eerie,dynamic,motion,striking,awe-inspiring,nightmarish,nightmarish,nightmare,horrifying,bio-mechanical,body horror,amalgamation", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 20 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-02-14T20:09:05.181383Z", "created_at": "2024-02-14T20:08:54.561449Z", "data_removed": false, "error": null, "id": "aobq2r3b6m3fvdkaizg6jj77qe", "input": { "width": 1024, "height": 1024, "prompt": "spacious,circular underground room,{dirtied white tiles},amalgamation,flesh,plastic,dark fabric,core,pulsating heart,limbs,human-like arms,twisted angelic wings,arms,covered in skin,feathers,scales,undulate slowly,unseen current,convulsing,head area,chaotic,mass of eyes,mouths,no human features,smaller forms,cherubs,demons,golden wires,surround,holy light,tv static effect,golden glow,shadows,terrifying essence,overwhelming presence,nightmarish,landscape,sparse,cavernous,eerie,dynamic,motion,striking,awe-inspiring,nightmarish,nightmarish,nightmare,horrifying,bio-mechanical,body horror,amalgamation", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 20 }, "logs": "Using seed: 3758746546\nPrompt: spacious,circular underground room,{dirtied white tiles},amalgamation,flesh,plastic,dark fabric,core,pulsating heart,limbs,human-like arms,twisted angelic wings,arms,covered in skin,feathers,scales,undulate slowly,unseen current,convulsing,head area,chaotic,mass of eyes,mouths,no human features,smaller forms,cherubs,demons,golden wires,surround,holy light,tv static effect,golden glow,shadows,terrifying essence,overwhelming presence,nightmarish,landscape,sparse,cavernous,eerie,dynamic,motion,striking,awe-inspiring,nightmarish,nightmarish,nightmare,horrifying,bio-mechanical,body horror,amalgamation\ntxt2img mode\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['no human features, smaller forms, cherubs, demons, golden wires, surround, holy light, tv static effect, golden glow, shadows, terrifying essence, overwhelming presence, nightmarish, landscape, sparse, cavernous, eerie, dynamic, motion, striking, awe - inspiring, nightmarish, nightmarish, nightmare, horrifying, bio - mechanical, body horror, amalgamation']\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['no human features, smaller forms, cherubs, demons, golden wires, surround, holy light, tv static effect, golden glow, shadows, terrifying essence, overwhelming presence, nightmarish, landscape, sparse, cavernous, eerie, dynamic, motion, striking, awe - inspiring, nightmarish, nightmarish, nightmare, horrifying, bio - mechanical, body horror, amalgamation']\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:07, 2.48it/s]\n 10%|█ | 2/20 [00:00<00:07, 2.48it/s]\n 15%|█▌ | 3/20 [00:01<00:06, 2.47it/s]\n 20%|██ | 4/20 [00:01<00:06, 2.47it/s]\n 25%|██▌ | 5/20 [00:02<00:06, 2.47it/s]\n 30%|███ | 6/20 [00:02<00:05, 2.47it/s]\n 35%|███▌ | 7/20 [00:02<00:05, 2.47it/s]\n 40%|████ | 8/20 [00:03<00:04, 2.47it/s]\n 45%|████▌ | 9/20 [00:03<00:04, 2.47it/s]\n 50%|█████ | 10/20 [00:04<00:04, 2.47it/s]\n 55%|█████▌ | 11/20 [00:04<00:03, 2.47it/s]\n 60%|██████ | 12/20 [00:04<00:03, 2.47it/s]\n 65%|██████▌ | 13/20 [00:05<00:02, 2.46it/s]\n 70%|███████ | 14/20 [00:05<00:02, 2.46it/s]\n 75%|███████▌ | 15/20 [00:06<00:02, 2.46it/s]\n 80%|████████ | 16/20 [00:06<00:01, 2.46it/s]\n 85%|████████▌ | 17/20 [00:06<00:01, 2.46it/s]\n 90%|█████████ | 18/20 [00:07<00:00, 2.46it/s]\n 95%|█████████▌| 19/20 [00:07<00:00, 2.46it/s]\n100%|██████████| 20/20 [00:07<00:00, 2.89it/s]\n100%|██████████| 20/20 [00:07<00:00, 2.53it/s]", "metrics": { "predict_time": 10.583868, "total_time": 10.619934 }, "output": [ "https://replicate.delivery/pbxt/KLeR6H1freGlaIRwIOOgDaSSJCG3HHeqiaGY4z8RA1T99zaJB/out-0.png" ], "started_at": "2024-02-14T20:08:54.597515Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/aobq2r3b6m3fvdkaizg6jj77qe", "cancel": "https://api.replicate.com/v1/predictions/aobq2r3b6m3fvdkaizg6jj77qe/cancel" }, "version": "b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48" }
Generated inUsing seed: 3758746546 Prompt: spacious,circular underground room,{dirtied white tiles},amalgamation,flesh,plastic,dark fabric,core,pulsating heart,limbs,human-like arms,twisted angelic wings,arms,covered in skin,feathers,scales,undulate slowly,unseen current,convulsing,head area,chaotic,mass of eyes,mouths,no human features,smaller forms,cherubs,demons,golden wires,surround,holy light,tv static effect,golden glow,shadows,terrifying essence,overwhelming presence,nightmarish,landscape,sparse,cavernous,eerie,dynamic,motion,striking,awe-inspiring,nightmarish,nightmarish,nightmare,horrifying,bio-mechanical,body horror,amalgamation txt2img mode The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['no human features, smaller forms, cherubs, demons, golden wires, surround, holy light, tv static effect, golden glow, shadows, terrifying essence, overwhelming presence, nightmarish, landscape, sparse, cavernous, eerie, dynamic, motion, striking, awe - inspiring, nightmarish, nightmarish, nightmare, horrifying, bio - mechanical, body horror, amalgamation'] The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['no human features, smaller forms, cherubs, demons, golden wires, surround, holy light, tv static effect, golden glow, shadows, terrifying essence, overwhelming presence, nightmarish, landscape, sparse, cavernous, eerie, dynamic, motion, striking, awe - inspiring, nightmarish, nightmarish, nightmare, horrifying, bio - mechanical, body horror, amalgamation'] 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:07, 2.48it/s] 10%|█ | 2/20 [00:00<00:07, 2.48it/s] 15%|█▌ | 3/20 [00:01<00:06, 2.47it/s] 20%|██ | 4/20 [00:01<00:06, 2.47it/s] 25%|██▌ | 5/20 [00:02<00:06, 2.47it/s] 30%|███ | 6/20 [00:02<00:05, 2.47it/s] 35%|███▌ | 7/20 [00:02<00:05, 2.47it/s] 40%|████ | 8/20 [00:03<00:04, 2.47it/s] 45%|████▌ | 9/20 [00:03<00:04, 2.47it/s] 50%|█████ | 10/20 [00:04<00:04, 2.47it/s] 55%|█████▌ | 11/20 [00:04<00:03, 2.47it/s] 60%|██████ | 12/20 [00:04<00:03, 2.47it/s] 65%|██████▌ | 13/20 [00:05<00:02, 2.46it/s] 70%|███████ | 14/20 [00:05<00:02, 2.46it/s] 75%|███████▌ | 15/20 [00:06<00:02, 2.46it/s] 80%|████████ | 16/20 [00:06<00:01, 2.46it/s] 85%|████████▌ | 17/20 [00:06<00:01, 2.46it/s] 90%|█████████ | 18/20 [00:07<00:00, 2.46it/s] 95%|█████████▌| 19/20 [00:07<00:00, 2.46it/s] 100%|██████████| 20/20 [00:07<00:00, 2.89it/s] 100%|██████████| 20/20 [00:07<00:00, 2.53it/s]
Prediction
datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48IDluizl43btallwanbemwncvmxzaStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- A robot holding a sign saying 'The Application did not respond' in red colors
- scheduler
- DPM++2MSDE
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- negative_prompt
- nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 1024, "height": 1024, "prompt": "A robot holding a sign saying 'The Application did not respond' in red colors", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run datacte/proteus-v0.3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", { input: { width: 1024, height: 1024, prompt: "A robot holding a sign saying 'The Application did not respond' in red colors", scheduler: "DPM++2MSDE", num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, negative_prompt: "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", prompt_strength: 0.8, num_inference_steps: 30 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run datacte/proteus-v0.3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", input={ "width": 1024, "height": 1024, "prompt": "A robot holding a sign saying 'The Application did not respond' in red colors", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run datacte/proteus-v0.3 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": "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", "input": { "width": 1024, "height": 1024, "prompt": "A robot holding a sign saying \'The Application did not respond\' in red colors", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/datacte/proteus-v0.3@sha256:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48 \ -i 'width=1024' \ -i 'height=1024' \ -i $'prompt="A robot holding a sign saying \'The Application did not respond\' in red colors"' \ -i 'scheduler="DPM++2MSDE"' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=true' \ -i 'negative_prompt="nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=30'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/datacte/proteus-v0.3@sha256:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "A robot holding a sign saying \'The Application did not respond\' in red colors", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-02-14T20:13:25.931736Z", "created_at": "2024-02-14T20:13:11.527614Z", "data_removed": false, "error": null, "id": "luizl43btallwanbemwncvmxza", "input": { "width": 1024, "height": 1024, "prompt": "A robot holding a sign saying 'The Application did not respond' in red colors", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 3817601993\nPrompt: A robot holding a sign saying 'The Application did not respond' in red colors\ntxt2img mode\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:11, 2.48it/s]\n 7%|▋ | 2/30 [00:00<00:11, 2.48it/s]\n 10%|█ | 3/30 [00:01<00:10, 2.47it/s]\n 13%|█▎ | 4/30 [00:01<00:10, 2.47it/s]\n 17%|█▋ | 5/30 [00:02<00:10, 2.47it/s]\n 20%|██ | 6/30 [00:02<00:09, 2.47it/s]\n 23%|██▎ | 7/30 [00:02<00:09, 2.47it/s]\n 27%|██▋ | 8/30 [00:03<00:08, 2.47it/s]\n 30%|███ | 9/30 [00:03<00:08, 2.47it/s]\n 33%|███▎ | 10/30 [00:04<00:08, 2.47it/s]\n 37%|███▋ | 11/30 [00:04<00:07, 2.47it/s]\n 40%|████ | 12/30 [00:04<00:07, 2.47it/s]\n 43%|████▎ | 13/30 [00:05<00:06, 2.46it/s]\n 47%|████▋ | 14/30 [00:05<00:06, 2.46it/s]\n 50%|█████ | 15/30 [00:06<00:06, 2.46it/s]\n 53%|█████▎ | 16/30 [00:06<00:05, 2.46it/s]\n 57%|█████▋ | 17/30 [00:06<00:05, 2.46it/s]\n 60%|██████ | 18/30 [00:07<00:04, 2.46it/s]\n 63%|██████▎ | 19/30 [00:07<00:04, 2.46it/s]\n 67%|██████▋ | 20/30 [00:08<00:04, 2.46it/s]\n 70%|███████ | 21/30 [00:08<00:03, 2.46it/s]\n 73%|███████▎ | 22/30 [00:08<00:03, 2.46it/s]\n 77%|███████▋ | 23/30 [00:09<00:02, 2.46it/s]\n 80%|████████ | 24/30 [00:09<00:02, 2.46it/s]\n 83%|████████▎ | 25/30 [00:10<00:02, 2.46it/s]\n 87%|████████▋ | 26/30 [00:10<00:01, 2.46it/s]\n 90%|█████████ | 27/30 [00:10<00:01, 2.46it/s]\n 93%|█████████▎| 28/30 [00:11<00:00, 2.45it/s]\n 97%|█████████▋| 29/30 [00:11<00:00, 2.45it/s]\n100%|██████████| 30/30 [00:11<00:00, 2.89it/s]\n100%|██████████| 30/30 [00:11<00:00, 2.50it/s]", "metrics": { "predict_time": 14.370009, "total_time": 14.404122 }, "output": [ "https://replicate.delivery/pbxt/OFTWAMyFi4o2NlyeUy0rbUNMCmTl75iOrFNZ9UGVobbyhWLJA/out-0.png" ], "started_at": "2024-02-14T20:13:11.561727Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/luizl43btallwanbemwncvmxza", "cancel": "https://api.replicate.com/v1/predictions/luizl43btallwanbemwncvmxza/cancel" }, "version": "b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48" }
Generated inUsing seed: 3817601993 Prompt: A robot holding a sign saying 'The Application did not respond' in red colors txt2img mode 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:11, 2.48it/s] 7%|▋ | 2/30 [00:00<00:11, 2.48it/s] 10%|█ | 3/30 [00:01<00:10, 2.47it/s] 13%|█▎ | 4/30 [00:01<00:10, 2.47it/s] 17%|█▋ | 5/30 [00:02<00:10, 2.47it/s] 20%|██ | 6/30 [00:02<00:09, 2.47it/s] 23%|██▎ | 7/30 [00:02<00:09, 2.47it/s] 27%|██▋ | 8/30 [00:03<00:08, 2.47it/s] 30%|███ | 9/30 [00:03<00:08, 2.47it/s] 33%|███▎ | 10/30 [00:04<00:08, 2.47it/s] 37%|███▋ | 11/30 [00:04<00:07, 2.47it/s] 40%|████ | 12/30 [00:04<00:07, 2.47it/s] 43%|████▎ | 13/30 [00:05<00:06, 2.46it/s] 47%|████▋ | 14/30 [00:05<00:06, 2.46it/s] 50%|█████ | 15/30 [00:06<00:06, 2.46it/s] 53%|█████▎ | 16/30 [00:06<00:05, 2.46it/s] 57%|█████▋ | 17/30 [00:06<00:05, 2.46it/s] 60%|██████ | 18/30 [00:07<00:04, 2.46it/s] 63%|██████▎ | 19/30 [00:07<00:04, 2.46it/s] 67%|██████▋ | 20/30 [00:08<00:04, 2.46it/s] 70%|███████ | 21/30 [00:08<00:03, 2.46it/s] 73%|███████▎ | 22/30 [00:08<00:03, 2.46it/s] 77%|███████▋ | 23/30 [00:09<00:02, 2.46it/s] 80%|████████ | 24/30 [00:09<00:02, 2.46it/s] 83%|████████▎ | 25/30 [00:10<00:02, 2.46it/s] 87%|████████▋ | 26/30 [00:10<00:01, 2.46it/s] 90%|█████████ | 27/30 [00:10<00:01, 2.46it/s] 93%|█████████▎| 28/30 [00:11<00:00, 2.45it/s] 97%|█████████▋| 29/30 [00:11<00:00, 2.45it/s] 100%|██████████| 30/30 [00:11<00:00, 2.89it/s] 100%|██████████| 30/30 [00:11<00:00, 2.50it/s]
Prediction
datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48IDulbmoudbfchn7qmesycscze6riStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- A photograph of Hughyen in his early twenties, (an inspiring artist whose art focuses on glitching images and vaporwave color gradients with unexpected conflicting compositions:0.5)
- scheduler
- DPM++2MSDE
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- negative_prompt
- nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 1024, "height": 1024, "prompt": "A photograph of Hughyen in his early twenties, (an inspiring artist whose art focuses on glitching images and vaporwave color gradients with unexpected conflicting compositions:0.5)", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run datacte/proteus-v0.3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", { input: { width: 1024, height: 1024, prompt: "A photograph of Hughyen in his early twenties, (an inspiring artist whose art focuses on glitching images and vaporwave color gradients with unexpected conflicting compositions:0.5)", scheduler: "DPM++2MSDE", num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, negative_prompt: "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", prompt_strength: 0.8, num_inference_steps: 30 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run datacte/proteus-v0.3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", input={ "width": 1024, "height": 1024, "prompt": "A photograph of Hughyen in his early twenties, (an inspiring artist whose art focuses on glitching images and vaporwave color gradients with unexpected conflicting compositions:0.5)", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run datacte/proteus-v0.3 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": "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", "input": { "width": 1024, "height": 1024, "prompt": "A photograph of Hughyen in his early twenties, (an inspiring artist whose art focuses on glitching images and vaporwave color gradients with unexpected conflicting compositions:0.5)", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/datacte/proteus-v0.3@sha256:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48 \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="A photograph of Hughyen in his early twenties, (an inspiring artist whose art focuses on glitching images and vaporwave color gradients with unexpected conflicting compositions:0.5)"' \ -i 'scheduler="DPM++2MSDE"' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=true' \ -i 'negative_prompt="nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=30'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/datacte/proteus-v0.3@sha256:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "A photograph of Hughyen in his early twenties, (an inspiring artist whose art focuses on glitching images and vaporwave color gradients with unexpected conflicting compositions:0.5)", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-02-14T20:13:59.015368Z", "created_at": "2024-02-14T20:13:44.405207Z", "data_removed": false, "error": null, "id": "ulbmoudbfchn7qmesycscze6ri", "input": { "width": 1024, "height": 1024, "prompt": "A photograph of Hughyen in his early twenties, (an inspiring artist whose art focuses on glitching images and vaporwave color gradients with unexpected conflicting compositions:0.5)", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 760119535\nPrompt: A photograph of Hughyen in his early twenties, (an inspiring artist whose art focuses on glitching images and vaporwave color gradients with unexpected conflicting compositions:0.5)\ntxt2img mode\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:11, 2.49it/s]\n 7%|▋ | 2/30 [00:00<00:11, 2.48it/s]\n 10%|█ | 3/30 [00:01<00:10, 2.46it/s]\n 13%|█▎ | 4/30 [00:01<00:10, 2.47it/s]\n 17%|█▋ | 5/30 [00:02<00:10, 2.48it/s]\n 20%|██ | 6/30 [00:02<00:09, 2.47it/s]\n 23%|██▎ | 7/30 [00:02<00:09, 2.48it/s]\n 27%|██▋ | 8/30 [00:03<00:08, 2.47it/s]\n 30%|███ | 9/30 [00:03<00:08, 2.47it/s]\n 33%|███▎ | 10/30 [00:04<00:08, 2.47it/s]\n 37%|███▋ | 11/30 [00:04<00:07, 2.47it/s]\n 40%|████ | 12/30 [00:04<00:07, 2.47it/s]\n 43%|████▎ | 13/30 [00:05<00:06, 2.47it/s]\n 47%|████▋ | 14/30 [00:05<00:06, 2.47it/s]\n 50%|█████ | 15/30 [00:06<00:06, 2.47it/s]\n 53%|█████▎ | 16/30 [00:06<00:05, 2.47it/s]\n 57%|█████▋ | 17/30 [00:06<00:05, 2.47it/s]\n 60%|██████ | 18/30 [00:07<00:04, 2.47it/s]\n 63%|██████▎ | 19/30 [00:07<00:04, 2.47it/s]\n 67%|██████▋ | 20/30 [00:08<00:04, 2.47it/s]\n 70%|███████ | 21/30 [00:08<00:03, 2.46it/s]\n 73%|███████▎ | 22/30 [00:08<00:03, 2.46it/s]\n 77%|███████▋ | 23/30 [00:09<00:02, 2.47it/s]\n 80%|████████ | 24/30 [00:09<00:02, 2.47it/s]\n 83%|████████▎ | 25/30 [00:10<00:02, 2.46it/s]\n 87%|████████▋ | 26/30 [00:10<00:01, 2.47it/s]\n 90%|█████████ | 27/30 [00:10<00:01, 2.47it/s]\n 93%|█████████▎| 28/30 [00:11<00:00, 2.46it/s]\n 97%|█████████▋| 29/30 [00:11<00:00, 2.46it/s]\n100%|██████████| 30/30 [00:11<00:00, 2.90it/s]\n100%|██████████| 30/30 [00:11<00:00, 2.51it/s]", "metrics": { "predict_time": 14.571392, "total_time": 14.610161 }, "output": [ "https://replicate.delivery/pbxt/wNNmrQXcTHYRKFGqKDr5pYiQ3BZWJGjvbpzBTUCxQBeCiWLJA/out-0.png" ], "started_at": "2024-02-14T20:13:44.443976Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ulbmoudbfchn7qmesycscze6ri", "cancel": "https://api.replicate.com/v1/predictions/ulbmoudbfchn7qmesycscze6ri/cancel" }, "version": "b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48" }
Generated inUsing seed: 760119535 Prompt: A photograph of Hughyen in his early twenties, (an inspiring artist whose art focuses on glitching images and vaporwave color gradients with unexpected conflicting compositions:0.5) txt2img mode 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:11, 2.49it/s] 7%|▋ | 2/30 [00:00<00:11, 2.48it/s] 10%|█ | 3/30 [00:01<00:10, 2.46it/s] 13%|█▎ | 4/30 [00:01<00:10, 2.47it/s] 17%|█▋ | 5/30 [00:02<00:10, 2.48it/s] 20%|██ | 6/30 [00:02<00:09, 2.47it/s] 23%|██▎ | 7/30 [00:02<00:09, 2.48it/s] 27%|██▋ | 8/30 [00:03<00:08, 2.47it/s] 30%|███ | 9/30 [00:03<00:08, 2.47it/s] 33%|███▎ | 10/30 [00:04<00:08, 2.47it/s] 37%|███▋ | 11/30 [00:04<00:07, 2.47it/s] 40%|████ | 12/30 [00:04<00:07, 2.47it/s] 43%|████▎ | 13/30 [00:05<00:06, 2.47it/s] 47%|████▋ | 14/30 [00:05<00:06, 2.47it/s] 50%|█████ | 15/30 [00:06<00:06, 2.47it/s] 53%|█████▎ | 16/30 [00:06<00:05, 2.47it/s] 57%|█████▋ | 17/30 [00:06<00:05, 2.47it/s] 60%|██████ | 18/30 [00:07<00:04, 2.47it/s] 63%|██████▎ | 19/30 [00:07<00:04, 2.47it/s] 67%|██████▋ | 20/30 [00:08<00:04, 2.47it/s] 70%|███████ | 21/30 [00:08<00:03, 2.46it/s] 73%|███████▎ | 22/30 [00:08<00:03, 2.46it/s] 77%|███████▋ | 23/30 [00:09<00:02, 2.47it/s] 80%|████████ | 24/30 [00:09<00:02, 2.47it/s] 83%|████████▎ | 25/30 [00:10<00:02, 2.46it/s] 87%|████████▋ | 26/30 [00:10<00:01, 2.47it/s] 90%|█████████ | 27/30 [00:10<00:01, 2.47it/s] 93%|█████████▎| 28/30 [00:11<00:00, 2.46it/s] 97%|█████████▋| 29/30 [00:11<00:00, 2.46it/s] 100%|██████████| 30/30 [00:11<00:00, 2.90it/s] 100%|██████████| 30/30 [00:11<00:00, 2.51it/s]
Prediction
datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48IDa27ybytbg6vejw5jujio5dciteStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- Glitch art. 1980s anime, vintage, analogue horror. ((static and noise)), chromatic aberration
- scheduler
- DPM++2MSDE
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- negative_prompt
- nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 1024, "height": 1024, "prompt": "Glitch art. 1980s anime, vintage, analogue horror. ((static and noise)), chromatic aberration", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run datacte/proteus-v0.3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", { input: { width: 1024, height: 1024, prompt: "Glitch art. 1980s anime, vintage, analogue horror. ((static and noise)), chromatic aberration", scheduler: "DPM++2MSDE", num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, negative_prompt: "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", prompt_strength: 0.8, num_inference_steps: 30 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run datacte/proteus-v0.3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", input={ "width": 1024, "height": 1024, "prompt": "Glitch art. 1980s anime, vintage, analogue horror. ((static and noise)), chromatic aberration", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run datacte/proteus-v0.3 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": "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", "input": { "width": 1024, "height": 1024, "prompt": "Glitch art. 1980s anime, vintage, analogue horror. ((static and noise)), chromatic aberration", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/datacte/proteus-v0.3@sha256:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48 \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="Glitch art. 1980s anime, vintage, analogue horror. ((static and noise)), chromatic aberration"' \ -i 'scheduler="DPM++2MSDE"' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=true' \ -i 'negative_prompt="nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=30'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/datacte/proteus-v0.3@sha256:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "Glitch art. 1980s anime, vintage, analogue horror. ((static and noise)), chromatic aberration", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-02-14T20:15:30.928577Z", "created_at": "2024-02-14T20:15:16.084483Z", "data_removed": false, "error": null, "id": "a27ybytbg6vejw5jujio5dcite", "input": { "width": 1024, "height": 1024, "prompt": "Glitch art. 1980s anime, vintage, analogue horror. ((static and noise)), chromatic aberration", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 2603207358\nPrompt: Glitch art. 1980s anime, vintage, analogue horror. ((static and noise)), chromatic aberration\ntxt2img mode\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:11, 2.51it/s]\n 7%|▋ | 2/30 [00:00<00:11, 2.50it/s]\n 10%|█ | 3/30 [00:01<00:10, 2.48it/s]\n 13%|█▎ | 4/30 [00:01<00:10, 2.48it/s]\n 17%|█▋ | 5/30 [00:02<00:10, 2.48it/s]\n 20%|██ | 6/30 [00:02<00:09, 2.47it/s]\n 23%|██▎ | 7/30 [00:02<00:09, 2.47it/s]\n 27%|██▋ | 8/30 [00:03<00:08, 2.47it/s]\n 30%|███ | 9/30 [00:03<00:08, 2.47it/s]\n 33%|███▎ | 10/30 [00:04<00:08, 2.47it/s]\n 37%|███▋ | 11/30 [00:04<00:07, 2.47it/s]\n 40%|████ | 12/30 [00:04<00:07, 2.47it/s]\n 43%|████▎ | 13/30 [00:05<00:06, 2.47it/s]\n 47%|████▋ | 14/30 [00:05<00:06, 2.47it/s]\n 50%|█████ | 15/30 [00:06<00:06, 2.46it/s]\n 53%|█████▎ | 16/30 [00:06<00:05, 2.46it/s]\n 57%|█████▋ | 17/30 [00:06<00:05, 2.46it/s]\n 60%|██████ | 18/30 [00:07<00:04, 2.46it/s]\n 63%|██████▎ | 19/30 [00:07<00:04, 2.46it/s]\n 67%|██████▋ | 20/30 [00:08<00:04, 2.46it/s]\n 70%|███████ | 21/30 [00:08<00:03, 2.46it/s]\n 73%|███████▎ | 22/30 [00:08<00:03, 2.46it/s]\n 77%|███████▋ | 23/30 [00:09<00:02, 2.46it/s]\n 80%|████████ | 24/30 [00:09<00:02, 2.46it/s]\n 83%|████████▎ | 25/30 [00:10<00:02, 2.46it/s]\n 87%|████████▋ | 26/30 [00:10<00:01, 2.46it/s]\n 90%|█████████ | 27/30 [00:10<00:01, 2.46it/s]\n 93%|█████████▎| 28/30 [00:11<00:00, 2.46it/s]\n 97%|█████████▋| 29/30 [00:11<00:00, 2.45it/s]\n100%|██████████| 30/30 [00:11<00:00, 2.89it/s]\n100%|██████████| 30/30 [00:11<00:00, 2.51it/s]", "metrics": { "predict_time": 14.809923, "total_time": 14.844094 }, "output": [ "https://replicate.delivery/pbxt/ZQbJiK3yDiKoOpHwE7ytoFNjMZXaKCLfYQaU7FU4UWowiWLJA/out-0.png" ], "started_at": "2024-02-14T20:15:16.118654Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/a27ybytbg6vejw5jujio5dcite", "cancel": "https://api.replicate.com/v1/predictions/a27ybytbg6vejw5jujio5dcite/cancel" }, "version": "b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48" }
Generated inUsing seed: 2603207358 Prompt: Glitch art. 1980s anime, vintage, analogue horror. ((static and noise)), chromatic aberration txt2img mode 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:11, 2.51it/s] 7%|▋ | 2/30 [00:00<00:11, 2.50it/s] 10%|█ | 3/30 [00:01<00:10, 2.48it/s] 13%|█▎ | 4/30 [00:01<00:10, 2.48it/s] 17%|█▋ | 5/30 [00:02<00:10, 2.48it/s] 20%|██ | 6/30 [00:02<00:09, 2.47it/s] 23%|██▎ | 7/30 [00:02<00:09, 2.47it/s] 27%|██▋ | 8/30 [00:03<00:08, 2.47it/s] 30%|███ | 9/30 [00:03<00:08, 2.47it/s] 33%|███▎ | 10/30 [00:04<00:08, 2.47it/s] 37%|███▋ | 11/30 [00:04<00:07, 2.47it/s] 40%|████ | 12/30 [00:04<00:07, 2.47it/s] 43%|████▎ | 13/30 [00:05<00:06, 2.47it/s] 47%|████▋ | 14/30 [00:05<00:06, 2.47it/s] 50%|█████ | 15/30 [00:06<00:06, 2.46it/s] 53%|█████▎ | 16/30 [00:06<00:05, 2.46it/s] 57%|█████▋ | 17/30 [00:06<00:05, 2.46it/s] 60%|██████ | 18/30 [00:07<00:04, 2.46it/s] 63%|██████▎ | 19/30 [00:07<00:04, 2.46it/s] 67%|██████▋ | 20/30 [00:08<00:04, 2.46it/s] 70%|███████ | 21/30 [00:08<00:03, 2.46it/s] 73%|███████▎ | 22/30 [00:08<00:03, 2.46it/s] 77%|███████▋ | 23/30 [00:09<00:02, 2.46it/s] 80%|████████ | 24/30 [00:09<00:02, 2.46it/s] 83%|████████▎ | 25/30 [00:10<00:02, 2.46it/s] 87%|████████▋ | 26/30 [00:10<00:01, 2.46it/s] 90%|█████████ | 27/30 [00:10<00:01, 2.46it/s] 93%|█████████▎| 28/30 [00:11<00:00, 2.46it/s] 97%|█████████▋| 29/30 [00:11<00:00, 2.45it/s] 100%|██████████| 30/30 [00:11<00:00, 2.89it/s] 100%|██████████| 30/30 [00:11<00:00, 2.51it/s]
Prediction
datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48IDjfskdbdbmalwtxrty3rmtlbyhyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- Masterpiece, glitch, holy holy holy, fog, by DarkIncursio
- scheduler
- DPM++2MSDE
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- negative_prompt
- nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 1024, "height": 1024, "prompt": "Masterpiece, glitch, holy holy holy, fog, by DarkIncursio", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run datacte/proteus-v0.3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", { input: { width: 1024, height: 1024, prompt: "Masterpiece, glitch, holy holy holy, fog, by DarkIncursio", scheduler: "DPM++2MSDE", num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, negative_prompt: "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", prompt_strength: 0.8, num_inference_steps: 30 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run datacte/proteus-v0.3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", input={ "width": 1024, "height": 1024, "prompt": "Masterpiece, glitch, holy holy holy, fog, by DarkIncursio", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run datacte/proteus-v0.3 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": "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", "input": { "width": 1024, "height": 1024, "prompt": "Masterpiece, glitch, holy holy holy, fog, by DarkIncursio", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/datacte/proteus-v0.3@sha256:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48 \ -i 'width=1024' \ -i 'height=1024' \ -i 'prompt="Masterpiece, glitch, holy holy holy, fog, by DarkIncursio"' \ -i 'scheduler="DPM++2MSDE"' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=true' \ -i 'negative_prompt="nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=30'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/datacte/proteus-v0.3@sha256:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "Masterpiece, glitch, holy holy holy, fog, by DarkIncursio", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-02-14T20:17:39.258901Z", "created_at": "2024-02-14T20:17:24.576320Z", "data_removed": false, "error": null, "id": "jfskdbdbmalwtxrty3rmtlbyhy", "input": { "width": 1024, "height": 1024, "prompt": "Masterpiece, glitch, holy holy holy, fog, by DarkIncursio", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 4016834622\nPrompt: Masterpiece, glitch, holy holy holy, fog, by DarkIncursio\ntxt2img mode\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:11, 2.51it/s]\n 7%|▋ | 2/30 [00:00<00:11, 2.50it/s]\n 10%|█ | 3/30 [00:01<00:10, 2.48it/s]\n 13%|█▎ | 4/30 [00:01<00:10, 2.48it/s]\n 17%|█▋ | 5/30 [00:02<00:10, 2.47it/s]\n 20%|██ | 6/30 [00:02<00:09, 2.47it/s]\n 23%|██▎ | 7/30 [00:02<00:09, 2.47it/s]\n 27%|██▋ | 8/30 [00:03<00:08, 2.47it/s]\n 30%|███ | 9/30 [00:03<00:08, 2.47it/s]\n 33%|███▎ | 10/30 [00:04<00:08, 2.47it/s]\n 37%|███▋ | 11/30 [00:04<00:07, 2.47it/s]\n 40%|████ | 12/30 [00:04<00:07, 2.47it/s]\n 43%|████▎ | 13/30 [00:05<00:06, 2.47it/s]\n 47%|████▋ | 14/30 [00:05<00:06, 2.47it/s]\n 50%|█████ | 15/30 [00:06<00:06, 2.47it/s]\n 53%|█████▎ | 16/30 [00:06<00:05, 2.47it/s]\n 57%|█████▋ | 17/30 [00:06<00:05, 2.47it/s]\n 60%|██████ | 18/30 [00:07<00:04, 2.46it/s]\n 63%|██████▎ | 19/30 [00:07<00:04, 2.47it/s]\n 67%|██████▋ | 20/30 [00:08<00:04, 2.47it/s]\n 70%|███████ | 21/30 [00:08<00:03, 2.46it/s]\n 73%|███████▎ | 22/30 [00:08<00:03, 2.46it/s]\n 77%|███████▋ | 23/30 [00:09<00:02, 2.46it/s]\n 80%|████████ | 24/30 [00:09<00:02, 2.46it/s]\n 83%|████████▎ | 25/30 [00:10<00:02, 2.46it/s]\n 87%|████████▋ | 26/30 [00:10<00:01, 2.46it/s]\n 90%|█████████ | 27/30 [00:10<00:01, 2.46it/s]\n 93%|█████████▎| 28/30 [00:11<00:00, 2.46it/s]\n 97%|█████████▋| 29/30 [00:11<00:00, 2.46it/s]\n100%|██████████| 30/30 [00:11<00:00, 2.90it/s]\n100%|██████████| 30/30 [00:11<00:00, 2.51it/s]", "metrics": { "predict_time": 14.617179, "total_time": 14.682581 }, "output": [ "https://replicate.delivery/pbxt/iL2qSzSFkJYKEFOQMZWwSHfYShN9ek3fgCffD42H15FO8o1SC/out-0.png" ], "started_at": "2024-02-14T20:17:24.641722Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/jfskdbdbmalwtxrty3rmtlbyhy", "cancel": "https://api.replicate.com/v1/predictions/jfskdbdbmalwtxrty3rmtlbyhy/cancel" }, "version": "b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48" }
Generated inUsing seed: 4016834622 Prompt: Masterpiece, glitch, holy holy holy, fog, by DarkIncursio txt2img mode 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:11, 2.51it/s] 7%|▋ | 2/30 [00:00<00:11, 2.50it/s] 10%|█ | 3/30 [00:01<00:10, 2.48it/s] 13%|█▎ | 4/30 [00:01<00:10, 2.48it/s] 17%|█▋ | 5/30 [00:02<00:10, 2.47it/s] 20%|██ | 6/30 [00:02<00:09, 2.47it/s] 23%|██▎ | 7/30 [00:02<00:09, 2.47it/s] 27%|██▋ | 8/30 [00:03<00:08, 2.47it/s] 30%|███ | 9/30 [00:03<00:08, 2.47it/s] 33%|███▎ | 10/30 [00:04<00:08, 2.47it/s] 37%|███▋ | 11/30 [00:04<00:07, 2.47it/s] 40%|████ | 12/30 [00:04<00:07, 2.47it/s] 43%|████▎ | 13/30 [00:05<00:06, 2.47it/s] 47%|████▋ | 14/30 [00:05<00:06, 2.47it/s] 50%|█████ | 15/30 [00:06<00:06, 2.47it/s] 53%|█████▎ | 16/30 [00:06<00:05, 2.47it/s] 57%|█████▋ | 17/30 [00:06<00:05, 2.47it/s] 60%|██████ | 18/30 [00:07<00:04, 2.46it/s] 63%|██████▎ | 19/30 [00:07<00:04, 2.47it/s] 67%|██████▋ | 20/30 [00:08<00:04, 2.47it/s] 70%|███████ | 21/30 [00:08<00:03, 2.46it/s] 73%|███████▎ | 22/30 [00:08<00:03, 2.46it/s] 77%|███████▋ | 23/30 [00:09<00:02, 2.46it/s] 80%|████████ | 24/30 [00:09<00:02, 2.46it/s] 83%|████████▎ | 25/30 [00:10<00:02, 2.46it/s] 87%|████████▋ | 26/30 [00:10<00:01, 2.46it/s] 90%|█████████ | 27/30 [00:10<00:01, 2.46it/s] 93%|█████████▎| 28/30 [00:11<00:00, 2.46it/s] 97%|█████████▋| 29/30 [00:11<00:00, 2.46it/s] 100%|██████████| 30/30 [00:11<00:00, 2.90it/s] 100%|██████████| 30/30 [00:11<00:00, 2.51it/s]
Prediction
datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48IDpwcksmtb6g6un4xjjn6repaxt4StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- Anime mugshot of a tough woman. She is holding a prison sign that reads "Proteus". Her face is censored. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)
- scheduler
- DPM++2MSDE
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- negative_prompt
- nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image
- prompt_strength
- 0.8
- num_inference_steps
- 30
{ "width": 1024, "height": 1024, "prompt": "Anime mugshot of a tough woman. She is holding a prison sign that reads \"Proteus\". Her face is censored. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run datacte/proteus-v0.3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", { input: { width: 1024, height: 1024, prompt: "Anime mugshot of a tough woman. She is holding a prison sign that reads \"Proteus\". Her face is censored. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)", scheduler: "DPM++2MSDE", num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, negative_prompt: "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", prompt_strength: 0.8, num_inference_steps: 30 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run datacte/proteus-v0.3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", input={ "width": 1024, "height": 1024, "prompt": "Anime mugshot of a tough woman. She is holding a prison sign that reads \"Proteus\". Her face is censored. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run datacte/proteus-v0.3 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": "datacte/proteus-v0.3:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48", "input": { "width": 1024, "height": 1024, "prompt": "Anime mugshot of a tough woman. She is holding a prison sign that reads \\"Proteus\\". Her face is censored. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/datacte/proteus-v0.3@sha256:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48 \ -i 'width=1024' \ -i 'height=1024' \ -i $'prompt="Anime mugshot of a tough woman. She is holding a prison sign that reads \\"Proteus\\". Her face is censored. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)"' \ -i 'scheduler="DPM++2MSDE"' \ -i 'num_outputs=1' \ -i 'guidance_scale=7.5' \ -i 'apply_watermark=true' \ -i 'negative_prompt="nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image"' \ -i 'prompt_strength=0.8' \ -i 'num_inference_steps=30'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/datacte/proteus-v0.3@sha256:b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 1024, "height": 1024, "prompt": "Anime mugshot of a tough woman. She is holding a prison sign that reads \\"Proteus\\". Her face is censored. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-02-14T20:25:53.267290Z", "created_at": "2024-02-14T20:24:47.803025Z", "data_removed": false, "error": null, "id": "pwcksmtb6g6un4xjjn6repaxt4", "input": { "width": 1024, "height": 1024, "prompt": "Anime mugshot of a tough woman. She is holding a prison sign that reads \"Proteus\". Her face is censored. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)", "scheduler": "DPM++2MSDE", "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "negative_prompt": "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image", "prompt_strength": 0.8, "num_inference_steps": 30 }, "logs": "Using seed: 1185096284\nPrompt: Anime mugshot of a tough woman. She is holding a prison sign that reads \"Proteus\". Her face is censored. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)\ntxt2img mode\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:15, 1.82it/s]\n 7%|▋ | 2/30 [00:00<00:12, 2.16it/s]\n 10%|█ | 3/30 [00:01<00:11, 2.30it/s]\n 13%|█▎ | 4/30 [00:01<00:10, 2.38it/s]\n 17%|█▋ | 5/30 [00:02<00:10, 2.41it/s]\n 20%|██ | 6/30 [00:02<00:09, 2.44it/s]\n 23%|██▎ | 7/30 [00:02<00:09, 2.45it/s]\n 27%|██▋ | 8/30 [00:03<00:08, 2.46it/s]\n 30%|███ | 9/30 [00:03<00:08, 2.47it/s]\n 33%|███▎ | 10/30 [00:04<00:08, 2.47it/s]\n 37%|███▋ | 11/30 [00:04<00:07, 2.47it/s]\n 40%|████ | 12/30 [00:04<00:07, 2.47it/s]\n 43%|████▎ | 13/30 [00:05<00:06, 2.47it/s]\n 47%|████▋ | 14/30 [00:05<00:06, 2.47it/s]\n 50%|█████ | 15/30 [00:06<00:06, 2.47it/s]\n 53%|█████▎ | 16/30 [00:06<00:05, 2.47it/s]\n 57%|█████▋ | 17/30 [00:06<00:05, 2.47it/s]\n 60%|██████ | 18/30 [00:07<00:04, 2.47it/s]\n 63%|██████▎ | 19/30 [00:07<00:04, 2.47it/s]\n 67%|██████▋ | 20/30 [00:08<00:04, 2.47it/s]\n 70%|███████ | 21/30 [00:08<00:03, 2.47it/s]\n 73%|███████▎ | 22/30 [00:09<00:03, 2.47it/s]\n 77%|███████▋ | 23/30 [00:09<00:02, 2.47it/s]\n 80%|████████ | 24/30 [00:09<00:02, 2.47it/s]\n 83%|████████▎ | 25/30 [00:10<00:02, 2.47it/s]\n 87%|████████▋ | 26/30 [00:10<00:01, 2.47it/s]\n 90%|█████████ | 27/30 [00:11<00:01, 2.47it/s]\n 93%|█████████▎| 28/30 [00:11<00:00, 2.46it/s]\n 97%|█████████▋| 29/30 [00:11<00:00, 2.47it/s]\n100%|██████████| 30/30 [00:12<00:00, 2.91it/s]\n100%|██████████| 30/30 [00:12<00:00, 2.49it/s]", "metrics": { "predict_time": 15.53602, "total_time": 65.464265 }, "output": [ "https://replicate.delivery/pbxt/C3LYYa30997dKRdeNDSXNjIK01CH5q8CSto12eWundnPPtWSA/out-0.png" ], "started_at": "2024-02-14T20:25:37.731270Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/pwcksmtb6g6un4xjjn6repaxt4", "cancel": "https://api.replicate.com/v1/predictions/pwcksmtb6g6un4xjjn6repaxt4/cancel" }, "version": "b28b79d725c8548b173b6a19ff9bffd16b9b80df5b18b8dc5cb9e1ee471bfa48" }
Generated inUsing seed: 1185096284 Prompt: Anime mugshot of a tough woman. She is holding a prison sign that reads "Proteus". Her face is censored. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2) txt2img mode 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:15, 1.82it/s] 7%|▋ | 2/30 [00:00<00:12, 2.16it/s] 10%|█ | 3/30 [00:01<00:11, 2.30it/s] 13%|█▎ | 4/30 [00:01<00:10, 2.38it/s] 17%|█▋ | 5/30 [00:02<00:10, 2.41it/s] 20%|██ | 6/30 [00:02<00:09, 2.44it/s] 23%|██▎ | 7/30 [00:02<00:09, 2.45it/s] 27%|██▋ | 8/30 [00:03<00:08, 2.46it/s] 30%|███ | 9/30 [00:03<00:08, 2.47it/s] 33%|███▎ | 10/30 [00:04<00:08, 2.47it/s] 37%|███▋ | 11/30 [00:04<00:07, 2.47it/s] 40%|████ | 12/30 [00:04<00:07, 2.47it/s] 43%|████▎ | 13/30 [00:05<00:06, 2.47it/s] 47%|████▋ | 14/30 [00:05<00:06, 2.47it/s] 50%|█████ | 15/30 [00:06<00:06, 2.47it/s] 53%|█████▎ | 16/30 [00:06<00:05, 2.47it/s] 57%|█████▋ | 17/30 [00:06<00:05, 2.47it/s] 60%|██████ | 18/30 [00:07<00:04, 2.47it/s] 63%|██████▎ | 19/30 [00:07<00:04, 2.47it/s] 67%|██████▋ | 20/30 [00:08<00:04, 2.47it/s] 70%|███████ | 21/30 [00:08<00:03, 2.47it/s] 73%|███████▎ | 22/30 [00:09<00:03, 2.47it/s] 77%|███████▋ | 23/30 [00:09<00:02, 2.47it/s] 80%|████████ | 24/30 [00:09<00:02, 2.47it/s] 83%|████████▎ | 25/30 [00:10<00:02, 2.47it/s] 87%|████████▋ | 26/30 [00:10<00:01, 2.47it/s] 90%|█████████ | 27/30 [00:11<00:01, 2.47it/s] 93%|█████████▎| 28/30 [00:11<00:00, 2.46it/s] 97%|█████████▋| 29/30 [00:11<00:00, 2.47it/s] 100%|██████████| 30/30 [00:12<00:00, 2.91it/s] 100%|██████████| 30/30 [00:12<00:00, 2.49it/s]
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