anotherjesse / sdv2-preview
Stable Diffusion 2.0 Preview
Prediction
anotherjesse/sdv2-preview:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5eIDrio3gcv6indwrk5hk65cu7op5iStatusSucceededSourceWebHardware–Total durationCreatedInput
- width
- "512"
- height
- 512
- prompt
- an concept art of the cat king, pale hair, one eye, intricate details, detailed face, detailed armour, artstation, epic pose, ambient light, by eiichiro oda
- num_outputs
- "1"
- guidance_scale
- 7.5
- num_inference_steps
- 50
{ "width": "512", "height": 512, "prompt": "an concept art of the cat king, pale hair, one eye, intricate details, detailed face, detailed armour, artstation, epic pose, ambient light, by eiichiro oda ", "num_outputs": "1", "guidance_scale": 7.5, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run anotherjesse/sdv2-preview using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "anotherjesse/sdv2-preview:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e", { input: { width: "512", height: 512, prompt: "an concept art of the cat king, pale hair, one eye, intricate details, detailed face, detailed armour, artstation, epic pose, ambient light, by eiichiro oda ", num_outputs: "1", guidance_scale: 7.5, num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run anotherjesse/sdv2-preview using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "anotherjesse/sdv2-preview:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e", input={ "width": "512", "height": 512, "prompt": "an concept art of the cat king, pale hair, one eye, intricate details, detailed face, detailed armour, artstation, epic pose, ambient light, by eiichiro oda ", "num_outputs": "1", "guidance_scale": 7.5, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run anotherjesse/sdv2-preview 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": "anotherjesse/sdv2-preview:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e", "input": { "width": "512", "height": 512, "prompt": "an concept art of the cat king, pale hair, one eye, intricate details, detailed face, detailed armour, artstation, epic pose, ambient light, by eiichiro oda ", "num_outputs": "1", "guidance_scale": 7.5, "num_inference_steps": 50 } }' \ 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/anotherjesse/sdv2-preview@sha256:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e \ -i 'width="512"' \ -i 'height=512' \ -i 'prompt="an concept art of the cat king, pale hair, one eye, intricate details, detailed face, detailed armour, artstation, epic pose, ambient light, by eiichiro oda "' \ -i 'num_outputs="1"' \ -i 'guidance_scale=7.5' \ -i 'num_inference_steps=50'
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/anotherjesse/sdv2-preview@sha256:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": "512", "height": 512, "prompt": "an concept art of the cat king, pale hair, one eye, intricate details, detailed face, detailed armour, artstation, epic pose, ambient light, by eiichiro oda ", "num_outputs": "1", "guidance_scale": 7.5, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2022-11-24T06:03:40.523373Z", "created_at": "2022-11-24T06:03:35.999117Z", "data_removed": false, "error": null, "id": "rio3gcv6indwrk5hk65cu7op5i", "input": { "width": "512", "height": 512, "prompt": "an concept art of the cat king, pale hair, one eye, intricate details, detailed face, detailed armour, artstation, epic pose, ambient light, by eiichiro oda ", "num_outputs": "1", "guidance_scale": 7.5, "num_inference_steps": 50 }, "logs": "Using seed: 32970\nGlobal seed set to 32970\nData shape for DDIM sampling is (1, 4, 64, 64), eta 0.0\nRunning DDIM Sampling with 50 timesteps\nDDIM Sampler: 0%| | 0/50 [00:00<?, ?it/s]\nDDIM Sampler: 4%|▍ | 2/50 [00:00<00:03, 13.25it/s]\nDDIM Sampler: 8%|▊ | 4/50 [00:00<00:03, 14.01it/s]\nDDIM Sampler: 12%|█▏ | 6/50 [00:00<00:03, 14.41it/s]\nDDIM Sampler: 16%|█▌ | 8/50 [00:00<00:03, 13.96it/s]\nDDIM Sampler: 20%|██ | 10/50 [00:00<00:02, 14.16it/s]\nDDIM Sampler: 24%|██▍ | 12/50 [00:00<00:02, 14.23it/s]\nDDIM Sampler: 28%|██▊ | 14/50 [00:00<00:02, 14.38it/s]\nDDIM Sampler: 32%|███▏ | 16/50 [00:01<00:02, 14.33it/s]\nDDIM Sampler: 36%|███▌ | 18/50 [00:01<00:02, 14.19it/s]\nDDIM Sampler: 40%|████ | 20/50 [00:01<00:02, 14.13it/s]\nDDIM Sampler: 44%|████▍ | 22/50 [00:01<00:01, 14.23it/s]\nDDIM Sampler: 48%|████▊ | 24/50 [00:01<00:01, 14.33it/s]\nDDIM Sampler: 52%|█████▏ | 26/50 [00:01<00:01, 14.39it/s]\nDDIM Sampler: 56%|█████▌ | 28/50 [00:01<00:01, 14.27it/s]\nDDIM Sampler: 60%|██████ | 30/50 [00:02<00:01, 14.35it/s]\nDDIM Sampler: 64%|██████▍ | 32/50 [00:02<00:01, 14.44it/s]\nDDIM Sampler: 68%|██████▊ | 34/50 [00:02<00:01, 14.39it/s]\nDDIM Sampler: 72%|███████▏ | 36/50 [00:02<00:00, 14.56it/s]\nDDIM Sampler: 76%|███████▌ | 38/50 [00:02<00:00, 14.69it/s]\nDDIM Sampler: 80%|████████ | 40/50 [00:02<00:00, 14.41it/s]\nDDIM Sampler: 84%|████████▍ | 42/50 [00:02<00:00, 14.49it/s]\nDDIM Sampler: 88%|████████▊ | 44/50 [00:03<00:00, 14.51it/s]\nDDIM Sampler: 92%|█████████▏| 46/50 [00:03<00:00, 14.59it/s]\nDDIM Sampler: 96%|█████████▌| 48/50 [00:03<00:00, 14.53it/s]\nDDIM Sampler: 100%|██████████| 50/50 [00:03<00:00, 14.48it/s]\nDDIM Sampler: 100%|██████████| 50/50 [00:03<00:00, 14.36it/s]", "metrics": { "predict_time": 4.488776, "total_time": 4.524256 }, "output": [ "https://replicate.delivery/pbxt/3JlNy0OCE6JZFN2huaoJFjfGO9tDRHRDQs6QIWeRoEP7sLDQA/out-0.png" ], "started_at": "2022-11-24T06:03:36.034597Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/rio3gcv6indwrk5hk65cu7op5i", "cancel": "https://api.replicate.com/v1/predictions/rio3gcv6indwrk5hk65cu7op5i/cancel" }, "version": "9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e" }
Generated inUsing seed: 32970 Global seed set to 32970 Data shape for DDIM sampling is (1, 4, 64, 64), eta 0.0 Running DDIM Sampling with 50 timesteps DDIM Sampler: 0%| | 0/50 [00:00<?, ?it/s] DDIM Sampler: 4%|▍ | 2/50 [00:00<00:03, 13.25it/s] DDIM Sampler: 8%|▊ | 4/50 [00:00<00:03, 14.01it/s] DDIM Sampler: 12%|█▏ | 6/50 [00:00<00:03, 14.41it/s] DDIM Sampler: 16%|█▌ | 8/50 [00:00<00:03, 13.96it/s] DDIM Sampler: 20%|██ | 10/50 [00:00<00:02, 14.16it/s] DDIM Sampler: 24%|██▍ | 12/50 [00:00<00:02, 14.23it/s] DDIM Sampler: 28%|██▊ | 14/50 [00:00<00:02, 14.38it/s] DDIM Sampler: 32%|███▏ | 16/50 [00:01<00:02, 14.33it/s] DDIM Sampler: 36%|███▌ | 18/50 [00:01<00:02, 14.19it/s] DDIM Sampler: 40%|████ | 20/50 [00:01<00:02, 14.13it/s] DDIM Sampler: 44%|████▍ | 22/50 [00:01<00:01, 14.23it/s] DDIM Sampler: 48%|████▊ | 24/50 [00:01<00:01, 14.33it/s] DDIM Sampler: 52%|█████▏ | 26/50 [00:01<00:01, 14.39it/s] DDIM Sampler: 56%|█████▌ | 28/50 [00:01<00:01, 14.27it/s] DDIM Sampler: 60%|██████ | 30/50 [00:02<00:01, 14.35it/s] DDIM Sampler: 64%|██████▍ | 32/50 [00:02<00:01, 14.44it/s] DDIM Sampler: 68%|██████▊ | 34/50 [00:02<00:01, 14.39it/s] DDIM Sampler: 72%|███████▏ | 36/50 [00:02<00:00, 14.56it/s] DDIM Sampler: 76%|███████▌ | 38/50 [00:02<00:00, 14.69it/s] DDIM Sampler: 80%|████████ | 40/50 [00:02<00:00, 14.41it/s] DDIM Sampler: 84%|████████▍ | 42/50 [00:02<00:00, 14.49it/s] DDIM Sampler: 88%|████████▊ | 44/50 [00:03<00:00, 14.51it/s] DDIM Sampler: 92%|█████████▏| 46/50 [00:03<00:00, 14.59it/s] DDIM Sampler: 96%|█████████▌| 48/50 [00:03<00:00, 14.53it/s] DDIM Sampler: 100%|██████████| 50/50 [00:03<00:00, 14.48it/s] DDIM Sampler: 100%|██████████| 50/50 [00:03<00:00, 14.36it/s]
Prediction
anotherjesse/sdv2-preview:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5eIDj5uyqgoacbg53fe3mzuocm5jg4StatusSucceededSourceWebHardware–Total durationCreatedInput
- width
- "768"
- height
- 512
- prompt
- anime key visual of portrait futuristic cyber warrior girl, in future cyberpunk tokyo rooftop, ssci - fi and fantasy, intricate and very very beautiful, neon light, highly detailed, digital painting, artstation, concept art, smooth, illustration, art by rossdraws and huaixuan xiang and alphonse mucha and wlop
- num_outputs
- "1"
- guidance_scale
- 7.5
- num_inference_steps
- 50
{ "width": "768", "height": 512, "prompt": "anime key visual of portrait futuristic cyber warrior girl, in future cyberpunk tokyo rooftop, ssci - fi and fantasy, intricate and very very beautiful, neon light, highly detailed, digital painting, artstation, concept art, smooth, illustration, art by rossdraws and huaixuan xiang and alphonse mucha and wlop ", "num_outputs": "1", "guidance_scale": 7.5, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run anotherjesse/sdv2-preview using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "anotherjesse/sdv2-preview:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e", { input: { width: "768", height: 512, prompt: "anime key visual of portrait futuristic cyber warrior girl, in future cyberpunk tokyo rooftop, ssci - fi and fantasy, intricate and very very beautiful, neon light, highly detailed, digital painting, artstation, concept art, smooth, illustration, art by rossdraws and huaixuan xiang and alphonse mucha and wlop ", num_outputs: "1", guidance_scale: 7.5, num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run anotherjesse/sdv2-preview using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "anotherjesse/sdv2-preview:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e", input={ "width": "768", "height": 512, "prompt": "anime key visual of portrait futuristic cyber warrior girl, in future cyberpunk tokyo rooftop, ssci - fi and fantasy, intricate and very very beautiful, neon light, highly detailed, digital painting, artstation, concept art, smooth, illustration, art by rossdraws and huaixuan xiang and alphonse mucha and wlop ", "num_outputs": "1", "guidance_scale": 7.5, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run anotherjesse/sdv2-preview 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": "anotherjesse/sdv2-preview:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e", "input": { "width": "768", "height": 512, "prompt": "anime key visual of portrait futuristic cyber warrior girl, in future cyberpunk tokyo rooftop, ssci - fi and fantasy, intricate and very very beautiful, neon light, highly detailed, digital painting, artstation, concept art, smooth, illustration, art by rossdraws and huaixuan xiang and alphonse mucha and wlop ", "num_outputs": "1", "guidance_scale": 7.5, "num_inference_steps": 50 } }' \ 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/anotherjesse/sdv2-preview@sha256:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e \ -i 'width="768"' \ -i 'height=512' \ -i 'prompt="anime key visual of portrait futuristic cyber warrior girl, in future cyberpunk tokyo rooftop, ssci - fi and fantasy, intricate and very very beautiful, neon light, highly detailed, digital painting, artstation, concept art, smooth, illustration, art by rossdraws and huaixuan xiang and alphonse mucha and wlop "' \ -i 'num_outputs="1"' \ -i 'guidance_scale=7.5' \ -i 'num_inference_steps=50'
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/anotherjesse/sdv2-preview@sha256:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": "768", "height": 512, "prompt": "anime key visual of portrait futuristic cyber warrior girl, in future cyberpunk tokyo rooftop, ssci - fi and fantasy, intricate and very very beautiful, neon light, highly detailed, digital painting, artstation, concept art, smooth, illustration, art by rossdraws and huaixuan xiang and alphonse mucha and wlop ", "num_outputs": "1", "guidance_scale": 7.5, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2022-11-24T06:04:24.331338Z", "created_at": "2022-11-24T06:04:18.960883Z", "data_removed": false, "error": null, "id": "j5uyqgoacbg53fe3mzuocm5jg4", "input": { "width": "768", "height": 512, "prompt": "anime key visual of portrait futuristic cyber warrior girl, in future cyberpunk tokyo rooftop, ssci - fi and fantasy, intricate and very very beautiful, neon light, highly detailed, digital painting, artstation, concept art, smooth, illustration, art by rossdraws and huaixuan xiang and alphonse mucha and wlop ", "num_outputs": "1", "guidance_scale": 7.5, "num_inference_steps": 50 }, "logs": "Using seed: 33138\nGlobal seed set to 33138\nData shape for DDIM sampling is (1, 4, 64, 96), eta 0.0\nRunning DDIM Sampling with 50 timesteps\nDDIM Sampler: 0%| | 0/50 [00:00<?, ?it/s]\nDDIM Sampler: 2%|▏ | 1/50 [00:00<00:07, 6.72it/s]\nDDIM Sampler: 6%|▌ | 3/50 [00:00<00:04, 10.21it/s]\nDDIM Sampler: 10%|█ | 5/50 [00:00<00:03, 11.31it/s]\nDDIM Sampler: 14%|█▍ | 7/50 [00:00<00:03, 11.85it/s]\nDDIM Sampler: 18%|█▊ | 9/50 [00:00<00:03, 12.14it/s]\nDDIM Sampler: 22%|██▏ | 11/50 [00:00<00:03, 12.04it/s]\nDDIM Sampler: 26%|██▌ | 13/50 [00:01<00:03, 12.18it/s]\nDDIM Sampler: 30%|███ | 15/50 [00:01<00:02, 12.02it/s]\nDDIM Sampler: 34%|███▍ | 17/50 [00:01<00:02, 12.05it/s]\nDDIM Sampler: 38%|███▊ | 19/50 [00:01<00:02, 12.24it/s]\nDDIM Sampler: 42%|████▏ | 21/50 [00:01<00:02, 12.37it/s]\nDDIM Sampler: 46%|████▌ | 23/50 [00:01<00:02, 12.45it/s]\nDDIM Sampler: 50%|█████ | 25/50 [00:02<00:02, 12.24it/s]\nDDIM Sampler: 54%|█████▍ | 27/50 [00:02<00:01, 12.31it/s]\nDDIM Sampler: 58%|█████▊ | 29/50 [00:02<00:01, 12.38it/s]\nDDIM Sampler: 62%|██████▏ | 31/50 [00:02<00:01, 12.46it/s]\nDDIM Sampler: 66%|██████▌ | 33/50 [00:02<00:01, 12.51it/s]\nDDIM Sampler: 70%|███████ | 35/50 [00:02<00:01, 12.27it/s]\nDDIM Sampler: 74%|███████▍ | 37/50 [00:03<00:01, 12.38it/s]\nDDIM Sampler: 78%|███████▊ | 39/50 [00:03<00:00, 12.41it/s]\nDDIM Sampler: 82%|████████▏ | 41/50 [00:03<00:00, 12.47it/s]\nDDIM Sampler: 86%|████████▌ | 43/50 [00:03<00:00, 12.47it/s]\nDDIM Sampler: 90%|█████████ | 45/50 [00:03<00:00, 12.30it/s]\nDDIM Sampler: 94%|█████████▍| 47/50 [00:03<00:00, 12.26it/s]\nDDIM Sampler: 98%|█████████▊| 49/50 [00:04<00:00, 12.30it/s]\nDDIM Sampler: 100%|██████████| 50/50 [00:04<00:00, 12.15it/s]", "metrics": { "predict_time": 5.335026, "total_time": 5.370455 }, "output": [ "https://replicate.delivery/pbxt/jqM0H0RJ7kJkGBnC1zVyoALkJ4L9Qa6ugySLbgUi8f6z2lBIA/out-0.png" ], "started_at": "2022-11-24T06:04:18.996312Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/j5uyqgoacbg53fe3mzuocm5jg4", "cancel": "https://api.replicate.com/v1/predictions/j5uyqgoacbg53fe3mzuocm5jg4/cancel" }, "version": "9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e" }
Generated inUsing seed: 33138 Global seed set to 33138 Data shape for DDIM sampling is (1, 4, 64, 96), eta 0.0 Running DDIM Sampling with 50 timesteps DDIM Sampler: 0%| | 0/50 [00:00<?, ?it/s] DDIM Sampler: 2%|▏ | 1/50 [00:00<00:07, 6.72it/s] DDIM Sampler: 6%|▌ | 3/50 [00:00<00:04, 10.21it/s] DDIM Sampler: 10%|█ | 5/50 [00:00<00:03, 11.31it/s] DDIM Sampler: 14%|█▍ | 7/50 [00:00<00:03, 11.85it/s] DDIM Sampler: 18%|█▊ | 9/50 [00:00<00:03, 12.14it/s] DDIM Sampler: 22%|██▏ | 11/50 [00:00<00:03, 12.04it/s] DDIM Sampler: 26%|██▌ | 13/50 [00:01<00:03, 12.18it/s] DDIM Sampler: 30%|███ | 15/50 [00:01<00:02, 12.02it/s] DDIM Sampler: 34%|███▍ | 17/50 [00:01<00:02, 12.05it/s] DDIM Sampler: 38%|███▊ | 19/50 [00:01<00:02, 12.24it/s] DDIM Sampler: 42%|████▏ | 21/50 [00:01<00:02, 12.37it/s] DDIM Sampler: 46%|████▌ | 23/50 [00:01<00:02, 12.45it/s] DDIM Sampler: 50%|█████ | 25/50 [00:02<00:02, 12.24it/s] DDIM Sampler: 54%|█████▍ | 27/50 [00:02<00:01, 12.31it/s] DDIM Sampler: 58%|█████▊ | 29/50 [00:02<00:01, 12.38it/s] DDIM Sampler: 62%|██████▏ | 31/50 [00:02<00:01, 12.46it/s] DDIM Sampler: 66%|██████▌ | 33/50 [00:02<00:01, 12.51it/s] DDIM Sampler: 70%|███████ | 35/50 [00:02<00:01, 12.27it/s] DDIM Sampler: 74%|███████▍ | 37/50 [00:03<00:01, 12.38it/s] DDIM Sampler: 78%|███████▊ | 39/50 [00:03<00:00, 12.41it/s] DDIM Sampler: 82%|████████▏ | 41/50 [00:03<00:00, 12.47it/s] DDIM Sampler: 86%|████████▌ | 43/50 [00:03<00:00, 12.47it/s] DDIM Sampler: 90%|█████████ | 45/50 [00:03<00:00, 12.30it/s] DDIM Sampler: 94%|█████████▍| 47/50 [00:03<00:00, 12.26it/s] DDIM Sampler: 98%|█████████▊| 49/50 [00:04<00:00, 12.30it/s] DDIM Sampler: 100%|██████████| 50/50 [00:04<00:00, 12.15it/s]
Prediction
anotherjesse/sdv2-preview:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5eIDrpxavif76vb2rkupxteubik7vyStatusSucceededSourceWebHardware–Total durationCreatedInput
- width
- "512"
- height
- 512
- prompt
- a highly detailed epic cinematic concept art CG render digital painting artwork: Yggdrasil kingdom. By Greg Rutkowski, in the style of Francis Bacon and Syd Mead and Norman Rockwell and Edward Hopper, open ceiling, highly detailed, painted by Francis Bacon and Edward Hopper, painted by James Gilleard, surrealism, airbrush, Ilya Kuvshinov, WLOP, Stanley Artgerm, very coherent, triadic color scheme, art by Takato Yamamoto and James Jean
- num_outputs
- "4"
- guidance_scale
- 7.5
- num_inference_steps
- 50
{ "width": "512", "height": 512, "prompt": "a highly detailed epic cinematic concept art CG render digital painting artwork: Yggdrasil kingdom. By Greg Rutkowski, in the style of Francis Bacon and Syd Mead and Norman Rockwell and Edward Hopper, open ceiling, highly detailed, painted by Francis Bacon and Edward Hopper, painted by James Gilleard, surrealism, airbrush, Ilya Kuvshinov, WLOP, Stanley Artgerm, very coherent, triadic color scheme, art by Takato Yamamoto and James Jean", "num_outputs": "4", "guidance_scale": 7.5, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run anotherjesse/sdv2-preview using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "anotherjesse/sdv2-preview:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e", { input: { width: "512", height: 512, prompt: "a highly detailed epic cinematic concept art CG render digital painting artwork: Yggdrasil kingdom. By Greg Rutkowski, in the style of Francis Bacon and Syd Mead and Norman Rockwell and Edward Hopper, open ceiling, highly detailed, painted by Francis Bacon and Edward Hopper, painted by James Gilleard, surrealism, airbrush, Ilya Kuvshinov, WLOP, Stanley Artgerm, very coherent, triadic color scheme, art by Takato Yamamoto and James Jean", num_outputs: "4", guidance_scale: 7.5, num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run anotherjesse/sdv2-preview using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "anotherjesse/sdv2-preview:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e", input={ "width": "512", "height": 512, "prompt": "a highly detailed epic cinematic concept art CG render digital painting artwork: Yggdrasil kingdom. By Greg Rutkowski, in the style of Francis Bacon and Syd Mead and Norman Rockwell and Edward Hopper, open ceiling, highly detailed, painted by Francis Bacon and Edward Hopper, painted by James Gilleard, surrealism, airbrush, Ilya Kuvshinov, WLOP, Stanley Artgerm, very coherent, triadic color scheme, art by Takato Yamamoto and James Jean", "num_outputs": "4", "guidance_scale": 7.5, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run anotherjesse/sdv2-preview 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": "anotherjesse/sdv2-preview:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e", "input": { "width": "512", "height": 512, "prompt": "a highly detailed epic cinematic concept art CG render digital painting artwork: Yggdrasil kingdom. By Greg Rutkowski, in the style of Francis Bacon and Syd Mead and Norman Rockwell and Edward Hopper, open ceiling, highly detailed, painted by Francis Bacon and Edward Hopper, painted by James Gilleard, surrealism, airbrush, Ilya Kuvshinov, WLOP, Stanley Artgerm, very coherent, triadic color scheme, art by Takato Yamamoto and James Jean", "num_outputs": "4", "guidance_scale": 7.5, "num_inference_steps": 50 } }' \ 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/anotherjesse/sdv2-preview@sha256:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e \ -i 'width="512"' \ -i 'height=512' \ -i 'prompt="a highly detailed epic cinematic concept art CG render digital painting artwork: Yggdrasil kingdom. By Greg Rutkowski, in the style of Francis Bacon and Syd Mead and Norman Rockwell and Edward Hopper, open ceiling, highly detailed, painted by Francis Bacon and Edward Hopper, painted by James Gilleard, surrealism, airbrush, Ilya Kuvshinov, WLOP, Stanley Artgerm, very coherent, triadic color scheme, art by Takato Yamamoto and James Jean"' \ -i 'num_outputs="4"' \ -i 'guidance_scale=7.5' \ -i 'num_inference_steps=50'
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/anotherjesse/sdv2-preview@sha256:9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": "512", "height": 512, "prompt": "a highly detailed epic cinematic concept art CG render digital painting artwork: Yggdrasil kingdom. By Greg Rutkowski, in the style of Francis Bacon and Syd Mead and Norman Rockwell and Edward Hopper, open ceiling, highly detailed, painted by Francis Bacon and Edward Hopper, painted by James Gilleard, surrealism, airbrush, Ilya Kuvshinov, WLOP, Stanley Artgerm, very coherent, triadic color scheme, art by Takato Yamamoto and James Jean", "num_outputs": "4", "guidance_scale": 7.5, "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2022-11-24T06:24:51.266596Z", "created_at": "2022-11-24T06:24:42.241082Z", "data_removed": false, "error": null, "id": "rpxavif76vb2rkupxteubik7vy", "input": { "width": "512", "height": 512, "prompt": "a highly detailed epic cinematic concept art CG render digital painting artwork: Yggdrasil kingdom. By Greg Rutkowski, in the style of Francis Bacon and Syd Mead and Norman Rockwell and Edward Hopper, open ceiling, highly detailed, painted by Francis Bacon and Edward Hopper, painted by James Gilleard, surrealism, airbrush, Ilya Kuvshinov, WLOP, Stanley Artgerm, very coherent, triadic color scheme, art by Takato Yamamoto and James Jean", "num_outputs": "4", "guidance_scale": 7.5, "num_inference_steps": 50 }, "logs": "Using seed: 52815\nGlobal seed set to 52815\nData shape for DDIM sampling is (4, 4, 64, 64), eta 0.0\nRunning DDIM Sampling with 50 timesteps\nDDIM Sampler: 0%| | 0/50 [00:00<?, ?it/s]\nDDIM Sampler: 2%|▏ | 1/50 [00:00<00:07, 6.26it/s]\nDDIM Sampler: 4%|▍ | 2/50 [00:00<00:07, 6.66it/s]\nDDIM Sampler: 6%|▌ | 3/50 [00:00<00:06, 6.95it/s]\nDDIM Sampler: 8%|▊ | 4/50 [00:00<00:06, 7.14it/s]\nDDIM Sampler: 10%|█ | 5/50 [00:00<00:06, 7.25it/s]\nDDIM Sampler: 12%|█▏ | 6/50 [00:00<00:06, 7.32it/s]\nDDIM Sampler: 14%|█▍ | 7/50 [00:00<00:05, 7.36it/s]\nDDIM Sampler: 16%|█▌ | 8/50 [00:01<00:05, 7.35it/s]\nDDIM Sampler: 18%|█▊ | 9/50 [00:01<00:05, 7.38it/s]\nDDIM Sampler: 20%|██ | 10/50 [00:01<00:05, 7.40it/s]\nDDIM Sampler: 22%|██▏ | 11/50 [00:01<00:05, 7.41it/s]\nDDIM Sampler: 24%|██▍ | 12/50 [00:01<00:05, 7.42it/s]\nDDIM Sampler: 26%|██▌ | 13/50 [00:01<00:04, 7.43it/s]\nDDIM Sampler: 28%|██▊ | 14/50 [00:01<00:04, 7.43it/s]\nDDIM Sampler: 30%|███ | 15/50 [00:02<00:04, 7.43it/s]\nDDIM Sampler: 32%|███▏ | 16/50 [00:02<00:04, 7.43it/s]\nDDIM Sampler: 34%|███▍ | 17/50 [00:02<00:04, 7.44it/s]\nDDIM Sampler: 36%|███▌ | 18/50 [00:02<00:04, 7.44it/s]\nDDIM Sampler: 38%|███▊ | 19/50 [00:02<00:04, 7.44it/s]\nDDIM Sampler: 40%|████ | 20/50 [00:02<00:04, 7.43it/s]\nDDIM Sampler: 42%|████▏ | 21/50 [00:02<00:03, 7.43it/s]\nDDIM Sampler: 44%|████▍ | 22/50 [00:02<00:03, 7.43it/s]\nDDIM Sampler: 46%|████▌ | 23/50 [00:03<00:03, 7.43it/s]\nDDIM Sampler: 48%|████▊ | 24/50 [00:03<00:03, 7.43it/s]\nDDIM Sampler: 50%|█████ | 25/50 [00:03<00:03, 7.43it/s]\nDDIM Sampler: 52%|█████▏ | 26/50 [00:03<00:03, 7.43it/s]\nDDIM Sampler: 54%|█████▍ | 27/50 [00:03<00:03, 7.43it/s]\nDDIM Sampler: 56%|█████▌ | 28/50 [00:03<00:02, 7.43it/s]\nDDIM Sampler: 58%|█████▊ | 29/50 [00:03<00:02, 7.42it/s]\nDDIM Sampler: 60%|██████ | 30/50 [00:04<00:02, 7.42it/s]\nDDIM Sampler: 62%|██████▏ | 31/50 [00:04<00:02, 7.42it/s]\nDDIM Sampler: 64%|██████▍ | 32/50 [00:04<00:02, 7.43it/s]\nDDIM Sampler: 66%|██████▌ | 33/50 [00:04<00:02, 7.43it/s]\nDDIM Sampler: 68%|██████▊ | 34/50 [00:04<00:02, 7.43it/s]\nDDIM Sampler: 70%|███████ | 35/50 [00:04<00:02, 7.43it/s]\nDDIM Sampler: 72%|███████▏ | 36/50 [00:04<00:01, 7.43it/s]\nDDIM Sampler: 74%|███████▍ | 37/50 [00:05<00:01, 7.43it/s]\nDDIM Sampler: 76%|███████▌ | 38/50 [00:05<00:01, 7.43it/s]\nDDIM Sampler: 78%|███████▊ | 39/50 [00:05<00:01, 7.42it/s]\nDDIM Sampler: 80%|████████ | 40/50 [00:05<00:01, 7.43it/s]\nDDIM Sampler: 82%|████████▏ | 41/50 [00:05<00:01, 7.43it/s]\nDDIM Sampler: 84%|████████▍ | 42/50 [00:05<00:01, 7.43it/s]\nDDIM Sampler: 86%|████████▌ | 43/50 [00:05<00:00, 7.44it/s]\nDDIM Sampler: 88%|████████▊ | 44/50 [00:05<00:00, 7.43it/s]\nDDIM Sampler: 90%|█████████ | 45/50 [00:06<00:00, 7.44it/s]\nDDIM Sampler: 92%|█████████▏| 46/50 [00:06<00:00, 7.43it/s]\nDDIM Sampler: 94%|█████████▍| 47/50 [00:06<00:00, 7.43it/s]\nDDIM Sampler: 96%|█████████▌| 48/50 [00:06<00:00, 7.43it/s]\nDDIM Sampler: 98%|█████████▊| 49/50 [00:06<00:00, 7.43it/s]\nDDIM Sampler: 100%|██████████| 50/50 [00:06<00:00, 7.43it/s]\nDDIM Sampler: 100%|██████████| 50/50 [00:06<00:00, 7.39it/s]", "metrics": { "predict_time": 8.990305, "total_time": 9.025514 }, "output": [ "https://replicate.delivery/pbxt/QDLyVZwlndKeCilfB8IqlFndBk1mlxoeLG3EhfQMNziLDwMAB/out-0.png", "https://replicate.delivery/pbxt/vuBnf6jlaOSbFSz1uPxAvJK0JzDfkS7243m45oGeiG1lBYGgA/out-1.png", "https://replicate.delivery/pbxt/sQXRNuCCAKpICJlRxbbtuMf7fMebI0EoPIWnKtDdbwVkBYGgA/out-2.png", "https://replicate.delivery/pbxt/NRPHeWG3Z2R0WSfSjcOFE5UYteagMWVb6F2WgpjCOY8mBYGgA/out-3.png" ], "started_at": "2022-11-24T06:24:42.276291Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/rpxavif76vb2rkupxteubik7vy", "cancel": "https://api.replicate.com/v1/predictions/rpxavif76vb2rkupxteubik7vy/cancel" }, "version": "9d608f854eed9805b26cdc3514a625d32f30f2c50075eb673f0c6541635c8c5e" }
Generated inUsing seed: 52815 Global seed set to 52815 Data shape for DDIM sampling is (4, 4, 64, 64), eta 0.0 Running DDIM Sampling with 50 timesteps DDIM Sampler: 0%| | 0/50 [00:00<?, ?it/s] DDIM Sampler: 2%|▏ | 1/50 [00:00<00:07, 6.26it/s] DDIM Sampler: 4%|▍ | 2/50 [00:00<00:07, 6.66it/s] DDIM Sampler: 6%|▌ | 3/50 [00:00<00:06, 6.95it/s] DDIM Sampler: 8%|▊ | 4/50 [00:00<00:06, 7.14it/s] DDIM Sampler: 10%|█ | 5/50 [00:00<00:06, 7.25it/s] DDIM Sampler: 12%|█▏ | 6/50 [00:00<00:06, 7.32it/s] DDIM Sampler: 14%|█▍ | 7/50 [00:00<00:05, 7.36it/s] DDIM Sampler: 16%|█▌ | 8/50 [00:01<00:05, 7.35it/s] DDIM Sampler: 18%|█▊ | 9/50 [00:01<00:05, 7.38it/s] DDIM Sampler: 20%|██ | 10/50 [00:01<00:05, 7.40it/s] DDIM Sampler: 22%|██▏ | 11/50 [00:01<00:05, 7.41it/s] DDIM Sampler: 24%|██▍ | 12/50 [00:01<00:05, 7.42it/s] DDIM Sampler: 26%|██▌ | 13/50 [00:01<00:04, 7.43it/s] DDIM Sampler: 28%|██▊ | 14/50 [00:01<00:04, 7.43it/s] DDIM Sampler: 30%|███ | 15/50 [00:02<00:04, 7.43it/s] DDIM Sampler: 32%|███▏ | 16/50 [00:02<00:04, 7.43it/s] DDIM Sampler: 34%|███▍ | 17/50 [00:02<00:04, 7.44it/s] DDIM Sampler: 36%|███▌ | 18/50 [00:02<00:04, 7.44it/s] DDIM Sampler: 38%|███▊ | 19/50 [00:02<00:04, 7.44it/s] DDIM Sampler: 40%|████ | 20/50 [00:02<00:04, 7.43it/s] DDIM Sampler: 42%|████▏ | 21/50 [00:02<00:03, 7.43it/s] DDIM Sampler: 44%|████▍ | 22/50 [00:02<00:03, 7.43it/s] DDIM Sampler: 46%|████▌ | 23/50 [00:03<00:03, 7.43it/s] DDIM Sampler: 48%|████▊ | 24/50 [00:03<00:03, 7.43it/s] DDIM Sampler: 50%|█████ | 25/50 [00:03<00:03, 7.43it/s] DDIM Sampler: 52%|█████▏ | 26/50 [00:03<00:03, 7.43it/s] DDIM Sampler: 54%|█████▍ | 27/50 [00:03<00:03, 7.43it/s] DDIM Sampler: 56%|█████▌ | 28/50 [00:03<00:02, 7.43it/s] DDIM Sampler: 58%|█████▊ | 29/50 [00:03<00:02, 7.42it/s] DDIM Sampler: 60%|██████ | 30/50 [00:04<00:02, 7.42it/s] DDIM Sampler: 62%|██████▏ | 31/50 [00:04<00:02, 7.42it/s] DDIM Sampler: 64%|██████▍ | 32/50 [00:04<00:02, 7.43it/s] DDIM Sampler: 66%|██████▌ | 33/50 [00:04<00:02, 7.43it/s] DDIM Sampler: 68%|██████▊ | 34/50 [00:04<00:02, 7.43it/s] DDIM Sampler: 70%|███████ | 35/50 [00:04<00:02, 7.43it/s] DDIM Sampler: 72%|███████▏ | 36/50 [00:04<00:01, 7.43it/s] DDIM Sampler: 74%|███████▍ | 37/50 [00:05<00:01, 7.43it/s] DDIM Sampler: 76%|███████▌ | 38/50 [00:05<00:01, 7.43it/s] DDIM Sampler: 78%|███████▊ | 39/50 [00:05<00:01, 7.42it/s] DDIM Sampler: 80%|████████ | 40/50 [00:05<00:01, 7.43it/s] DDIM Sampler: 82%|████████▏ | 41/50 [00:05<00:01, 7.43it/s] DDIM Sampler: 84%|████████▍ | 42/50 [00:05<00:01, 7.43it/s] DDIM Sampler: 86%|████████▌ | 43/50 [00:05<00:00, 7.44it/s] DDIM Sampler: 88%|████████▊ | 44/50 [00:05<00:00, 7.43it/s] DDIM Sampler: 90%|█████████ | 45/50 [00:06<00:00, 7.44it/s] DDIM Sampler: 92%|█████████▏| 46/50 [00:06<00:00, 7.43it/s] DDIM Sampler: 94%|█████████▍| 47/50 [00:06<00:00, 7.43it/s] DDIM Sampler: 96%|█████████▌| 48/50 [00:06<00:00, 7.43it/s] DDIM Sampler: 98%|█████████▊| 49/50 [00:06<00:00, 7.43it/s] DDIM Sampler: 100%|██████████| 50/50 [00:06<00:00, 7.43it/s] DDIM Sampler: 100%|██████████| 50/50 [00:06<00:00, 7.39it/s]
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