cjwbw
/
stable-diffusion-v2
sd-v2 with diffusers, test version!
- Public
- 280.3K runs
-
A100 (80GB)
Prediction
cjwbw/stable-diffusion-v2:e5e1fd33IDgxbijslwz5bbfffjr7y22j765eStatusSucceededSourceWebHardware–Total durationCreatedInput
- width
- "768"
- height
- 768
- prompt
- A fantasy landscape, trending on artstation
- scheduler
- DPMSolverMultistep
- num_outputs
- 1
- guidance_scale
- "6.55"
- prompt_strength
- 0.8
- num_inference_steps
- "50"
{ "width": "768", "height": 768, "prompt": "A fantasy landscape, trending on artstation", "scheduler": "DPMSolverMultistep", "init_image": "https://replicate.delivery/pbxt/HtCXRc5QMwvXfOOqx56gzsZcmTxmOwzSzN4CpzQj8q9pzaOt/sketch-mountains-input.jpeg", "num_outputs": 1, "guidance_scale": "6.55", "prompt_strength": 0.8, "num_inference_steps": "50" }
Install Replicate’s Node.js client library:npm install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run cjwbw/stable-diffusion-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cjwbw/stable-diffusion-v2:e5e1fd333a08c8035974a01dd42f799f1cca4625aec374643d716d9ae40cf2e4", { input: { width: "768", height: 768, prompt: "A fantasy landscape, trending on artstation", scheduler: "DPMSolverMultistep", init_image: "https://replicate.delivery/pbxt/HtCXRc5QMwvXfOOqx56gzsZcmTxmOwzSzN4CpzQj8q9pzaOt/sketch-mountains-input.jpeg", num_outputs: 1, guidance_scale: "6.55", prompt_strength: 0.8, num_inference_steps: "50" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the client:import replicate
Run cjwbw/stable-diffusion-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cjwbw/stable-diffusion-v2:e5e1fd333a08c8035974a01dd42f799f1cca4625aec374643d716d9ae40cf2e4", input={ "width": "768", "height": 768, "prompt": "A fantasy landscape, trending on artstation", "scheduler": "DPMSolverMultistep", "init_image": "https://replicate.delivery/pbxt/HtCXRc5QMwvXfOOqx56gzsZcmTxmOwzSzN4CpzQj8q9pzaOt/sketch-mountains-input.jpeg", "num_outputs": 1, "guidance_scale": "6.55", "prompt_strength": 0.8, "num_inference_steps": "50" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run cjwbw/stable-diffusion-v2 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": "e5e1fd333a08c8035974a01dd42f799f1cca4625aec374643d716d9ae40cf2e4", "input": { "width": "768", "height": 768, "prompt": "A fantasy landscape, trending on artstation", "scheduler": "DPMSolverMultistep", "init_image": "https://replicate.delivery/pbxt/HtCXRc5QMwvXfOOqx56gzsZcmTxmOwzSzN4CpzQj8q9pzaOt/sketch-mountains-input.jpeg", "num_outputs": 1, "guidance_scale": "6.55", "prompt_strength": 0.8, "num_inference_steps": "50" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-12-02T14:26:20.502898Z", "created_at": "2022-12-02T14:26:15.162182Z", "data_removed": false, "error": null, "id": "gxbijslwz5bbfffjr7y22j765e", "input": { "width": "768", "height": 768, "prompt": "A fantasy landscape, trending on artstation", "scheduler": "DPMSolverMultistep", "init_image": "https://replicate.delivery/pbxt/HtCXRc5QMwvXfOOqx56gzsZcmTxmOwzSzN4CpzQj8q9pzaOt/sketch-mountains-input.jpeg", "num_outputs": 1, "guidance_scale": "6.55", "prompt_strength": 0.8, "num_inference_steps": "50" }, "logs": "Using seed: 54338\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:04, 8.46it/s]\n 8%|▊ | 3/40 [00:00<00:03, 9.95it/s]\n 12%|█▎ | 5/40 [00:00<00:03, 10.28it/s]\n 18%|█▊ | 7/40 [00:00<00:03, 10.42it/s]\n 22%|██▎ | 9/40 [00:00<00:02, 10.49it/s]\n 28%|██▊ | 11/40 [00:01<00:02, 10.53it/s]\n 32%|███▎ | 13/40 [00:01<00:02, 10.55it/s]\n 38%|███▊ | 15/40 [00:01<00:02, 10.57it/s]\n 42%|████▎ | 17/40 [00:01<00:02, 10.58it/s]\n 48%|████▊ | 19/40 [00:01<00:01, 10.59it/s]\n 52%|█████▎ | 21/40 [00:02<00:01, 10.60it/s]\n 57%|█████▊ | 23/40 [00:02<00:01, 10.59it/s]\n 62%|██████▎ | 25/40 [00:02<00:01, 10.59it/s]\n 68%|██████▊ | 27/40 [00:02<00:01, 10.60it/s]\n 72%|███████▎ | 29/40 [00:02<00:01, 10.60it/s]\n 78%|███████▊ | 31/40 [00:02<00:00, 10.60it/s]\n 82%|████████▎ | 33/40 [00:03<00:00, 10.60it/s]\n 88%|████████▊ | 35/40 [00:03<00:00, 10.60it/s]\n 92%|█████████▎| 37/40 [00:03<00:00, 10.60it/s]\n 98%|█████████▊| 39/40 [00:03<00:00, 10.60it/s]\n100%|██████████| 40/40 [00:03<00:00, 10.54it/s]", "metrics": { "predict_time": 5.304438, "total_time": 5.340716 }, "output": [ "https://replicate.delivery/pbxt/EtsePYmau0VxLCzVZVafWf7WSYnu9NabtVrD7fJlD86uQvXAB/out-0.png" ], "started_at": "2022-12-02T14:26:15.198460Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/gxbijslwz5bbfffjr7y22j765e", "cancel": "https://api.replicate.com/v1/predictions/gxbijslwz5bbfffjr7y22j765e/cancel" }, "version": "e5e1fd333a08c8035974a01dd42f799f1cca4625aec374643d716d9ae40cf2e4" }
Generated inUsing seed: 54338 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:04, 8.46it/s] 8%|▊ | 3/40 [00:00<00:03, 9.95it/s] 12%|█▎ | 5/40 [00:00<00:03, 10.28it/s] 18%|█▊ | 7/40 [00:00<00:03, 10.42it/s] 22%|██▎ | 9/40 [00:00<00:02, 10.49it/s] 28%|██▊ | 11/40 [00:01<00:02, 10.53it/s] 32%|███▎ | 13/40 [00:01<00:02, 10.55it/s] 38%|███▊ | 15/40 [00:01<00:02, 10.57it/s] 42%|████▎ | 17/40 [00:01<00:02, 10.58it/s] 48%|████▊ | 19/40 [00:01<00:01, 10.59it/s] 52%|█████▎ | 21/40 [00:02<00:01, 10.60it/s] 57%|█████▊ | 23/40 [00:02<00:01, 10.59it/s] 62%|██████▎ | 25/40 [00:02<00:01, 10.59it/s] 68%|██████▊ | 27/40 [00:02<00:01, 10.60it/s] 72%|███████▎ | 29/40 [00:02<00:01, 10.60it/s] 78%|███████▊ | 31/40 [00:02<00:00, 10.60it/s] 82%|████████▎ | 33/40 [00:03<00:00, 10.60it/s] 88%|████████▊ | 35/40 [00:03<00:00, 10.60it/s] 92%|█████████▎| 37/40 [00:03<00:00, 10.60it/s] 98%|█████████▊| 39/40 [00:03<00:00, 10.60it/s] 100%|██████████| 40/40 [00:03<00:00, 10.54it/s]
Prediction
cjwbw/stable-diffusion-v2:e5e1fd33Input
- width
- 768
- height
- 768
- prompt
- a photo of an astronaut riding a horse on mars
- scheduler
- K_EULER
- num_outputs
- 1
- guidance_scale
- 7.5
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 768, "height": 768, "prompt": "a photo of an astronaut riding a horse on mars", "scheduler": "K_EULER", "num_outputs": 1, "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run cjwbw/stable-diffusion-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cjwbw/stable-diffusion-v2:e5e1fd333a08c8035974a01dd42f799f1cca4625aec374643d716d9ae40cf2e4", { input: { width: 768, height: 768, prompt: "a photo of an astronaut riding a horse on mars", scheduler: "K_EULER", num_outputs: 1, guidance_scale: 7.5, prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the client:import replicate
Run cjwbw/stable-diffusion-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cjwbw/stable-diffusion-v2:e5e1fd333a08c8035974a01dd42f799f1cca4625aec374643d716d9ae40cf2e4", input={ "width": 768, "height": 768, "prompt": "a photo of an astronaut riding a horse on mars", "scheduler": "K_EULER", "num_outputs": 1, "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run cjwbw/stable-diffusion-v2 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": "e5e1fd333a08c8035974a01dd42f799f1cca4625aec374643d716d9ae40cf2e4", "input": { "width": 768, "height": 768, "prompt": "a photo of an astronaut riding a horse on mars", "scheduler": "K_EULER", "num_outputs": 1, "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-11-24T19:33:41.949967Z", "created_at": "2022-11-24T19:33:34.583744Z", "data_removed": false, "error": null, "id": "w56jkpbhuvcm5brzppvzatscme", "input": { "width": 768, "height": 768, "prompt": "a photo of an astronaut riding a horse on mars", "scheduler": "K_EULER", "num_outputs": 1, "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 32989\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:07, 6.62it/s]\n 4%|▍ | 2/50 [00:00<00:06, 7.22it/s]\n 6%|▌ | 3/50 [00:00<00:06, 7.68it/s]\n 8%|▊ | 4/50 [00:00<00:05, 7.90it/s]\n 10%|█ | 5/50 [00:00<00:05, 8.04it/s]\n 12%|█▏ | 6/50 [00:00<00:05, 8.13it/s]\n 14%|█▍ | 7/50 [00:00<00:05, 8.18it/s]\n 16%|█▌ | 8/50 [00:01<00:05, 8.21it/s]\n 18%|█▊ | 9/50 [00:01<00:04, 8.23it/s]\n 20%|██ | 10/50 [00:01<00:04, 8.24it/s]\n 22%|██▏ | 11/50 [00:01<00:04, 8.26it/s]\n 24%|██▍ | 12/50 [00:01<00:04, 8.26it/s]\n 26%|██▌ | 13/50 [00:01<00:04, 8.28it/s]\n 28%|██▊ | 14/50 [00:01<00:04, 8.28it/s]\n 30%|███ | 15/50 [00:01<00:04, 8.27it/s]\n 32%|███▏ | 16/50 [00:01<00:04, 8.27it/s]\n 34%|███▍ | 17/50 [00:02<00:03, 8.26it/s]\n 36%|███▌ | 18/50 [00:02<00:03, 8.26it/s]\n 38%|███▊ | 19/50 [00:02<00:03, 8.27it/s]\n 40%|████ | 20/50 [00:02<00:03, 8.27it/s]\n 42%|████▏ | 21/50 [00:02<00:03, 8.27it/s]\n 44%|████▍ | 22/50 [00:02<00:03, 8.28it/s]\n 46%|████▌ | 23/50 [00:02<00:03, 8.28it/s]\n 48%|████▊ | 24/50 [00:02<00:03, 8.28it/s]\n 50%|█████ | 25/50 [00:03<00:03, 8.28it/s]\n 52%|█████▏ | 26/50 [00:03<00:02, 8.28it/s]\n 54%|█████▍ | 27/50 [00:03<00:02, 8.28it/s]\n 56%|█████▌ | 28/50 [00:03<00:02, 8.28it/s]\n 58%|█████▊ | 29/50 [00:03<00:02, 8.28it/s]\n 60%|██████ | 30/50 [00:03<00:02, 8.29it/s]\n 62%|██████▏ | 31/50 [00:03<00:02, 8.28it/s]\n 64%|██████▍ | 32/50 [00:03<00:02, 8.28it/s]\n 66%|██████▌ | 33/50 [00:04<00:02, 8.28it/s]\n 68%|██████▊ | 34/50 [00:04<00:01, 8.29it/s]\n 70%|███████ | 35/50 [00:04<00:01, 8.29it/s]\n 72%|███████▏ | 36/50 [00:04<00:01, 8.30it/s]\n 74%|███████▍ | 37/50 [00:04<00:01, 8.30it/s]\n 76%|███████▌ | 38/50 [00:04<00:01, 8.30it/s]\n 78%|███████▊ | 39/50 [00:04<00:01, 8.29it/s]\n 80%|████████ | 40/50 [00:04<00:01, 8.29it/s]\n 82%|████████▏ | 41/50 [00:04<00:01, 8.29it/s]\n 84%|████████▍ | 42/50 [00:05<00:00, 8.29it/s]\n 86%|████████▌ | 43/50 [00:05<00:00, 8.29it/s]\n 88%|████████▊ | 44/50 [00:05<00:00, 8.29it/s]\n 90%|█████████ | 45/50 [00:05<00:00, 8.29it/s]\n 92%|█████████▏| 46/50 [00:05<00:00, 8.30it/s]\n 94%|█████████▍| 47/50 [00:05<00:00, 8.30it/s]\n 96%|█████████▌| 48/50 [00:05<00:00, 8.30it/s]\n 98%|█████████▊| 49/50 [00:05<00:00, 8.30it/s]\n100%|██████████| 50/50 [00:06<00:00, 8.30it/s]\n100%|██████████| 50/50 [00:06<00:00, 8.23it/s]", "metrics": { "predict_time": 7.331184, "total_time": 7.366223 }, "output": [ "https://replicate.delivery/pbxt/Z1qXRKCfPlXuXKl2nhfb3eL3Y1TfqGylycuig9eClEOsi8aAC/out-0.png" ], "started_at": "2022-11-24T19:33:34.618783Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/w56jkpbhuvcm5brzppvzatscme", "cancel": "https://api.replicate.com/v1/predictions/w56jkpbhuvcm5brzppvzatscme/cancel" }, "version": "867f87d0d9a9bbef873e37bdf36c4835a01411c3bb18e43653d7de63fb536096" }
Generated inUsing seed: 32989 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:07, 6.62it/s] 4%|▍ | 2/50 [00:00<00:06, 7.22it/s] 6%|▌ | 3/50 [00:00<00:06, 7.68it/s] 8%|▊ | 4/50 [00:00<00:05, 7.90it/s] 10%|█ | 5/50 [00:00<00:05, 8.04it/s] 12%|█▏ | 6/50 [00:00<00:05, 8.13it/s] 14%|█▍ | 7/50 [00:00<00:05, 8.18it/s] 16%|█▌ | 8/50 [00:01<00:05, 8.21it/s] 18%|█▊ | 9/50 [00:01<00:04, 8.23it/s] 20%|██ | 10/50 [00:01<00:04, 8.24it/s] 22%|██▏ | 11/50 [00:01<00:04, 8.26it/s] 24%|██▍ | 12/50 [00:01<00:04, 8.26it/s] 26%|██▌ | 13/50 [00:01<00:04, 8.28it/s] 28%|██▊ | 14/50 [00:01<00:04, 8.28it/s] 30%|███ | 15/50 [00:01<00:04, 8.27it/s] 32%|███▏ | 16/50 [00:01<00:04, 8.27it/s] 34%|███▍ | 17/50 [00:02<00:03, 8.26it/s] 36%|███▌ | 18/50 [00:02<00:03, 8.26it/s] 38%|███▊ | 19/50 [00:02<00:03, 8.27it/s] 40%|████ | 20/50 [00:02<00:03, 8.27it/s] 42%|████▏ | 21/50 [00:02<00:03, 8.27it/s] 44%|████▍ | 22/50 [00:02<00:03, 8.28it/s] 46%|████▌ | 23/50 [00:02<00:03, 8.28it/s] 48%|████▊ | 24/50 [00:02<00:03, 8.28it/s] 50%|█████ | 25/50 [00:03<00:03, 8.28it/s] 52%|█████▏ | 26/50 [00:03<00:02, 8.28it/s] 54%|█████▍ | 27/50 [00:03<00:02, 8.28it/s] 56%|█████▌ | 28/50 [00:03<00:02, 8.28it/s] 58%|█████▊ | 29/50 [00:03<00:02, 8.28it/s] 60%|██████ | 30/50 [00:03<00:02, 8.29it/s] 62%|██████▏ | 31/50 [00:03<00:02, 8.28it/s] 64%|██████▍ | 32/50 [00:03<00:02, 8.28it/s] 66%|██████▌ | 33/50 [00:04<00:02, 8.28it/s] 68%|██████▊ | 34/50 [00:04<00:01, 8.29it/s] 70%|███████ | 35/50 [00:04<00:01, 8.29it/s] 72%|███████▏ | 36/50 [00:04<00:01, 8.30it/s] 74%|███████▍ | 37/50 [00:04<00:01, 8.30it/s] 76%|███████▌ | 38/50 [00:04<00:01, 8.30it/s] 78%|███████▊ | 39/50 [00:04<00:01, 8.29it/s] 80%|████████ | 40/50 [00:04<00:01, 8.29it/s] 82%|████████▏ | 41/50 [00:04<00:01, 8.29it/s] 84%|████████▍ | 42/50 [00:05<00:00, 8.29it/s] 86%|████████▌ | 43/50 [00:05<00:00, 8.29it/s] 88%|████████▊ | 44/50 [00:05<00:00, 8.29it/s] 90%|█████████ | 45/50 [00:05<00:00, 8.29it/s] 92%|█████████▏| 46/50 [00:05<00:00, 8.30it/s] 94%|█████████▍| 47/50 [00:05<00:00, 8.30it/s] 96%|█████████▌| 48/50 [00:05<00:00, 8.30it/s] 98%|█████████▊| 49/50 [00:05<00:00, 8.30it/s] 100%|██████████| 50/50 [00:06<00:00, 8.30it/s] 100%|██████████| 50/50 [00:06<00:00, 8.23it/s]
Prediction
cjwbw/stable-diffusion-v2:e5e1fd33IDcgtecb7rsncgdebsbiifkgfvtqStatusSucceededSourceWebHardware–Total durationCreatedInput
- width
- 768
- height
- 768
- prompt
- clear portrait of a superhero concept between spiderman and batman, cottagecore!!, background hyper detailed, character concept, full body, dynamic pose, intricate, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, art by artgerm and greg rutkowski and alphonse mucha
- scheduler
- K_EULER
- num_outputs
- 1
- guidance_scale
- 7.5
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 768, "height": 768, "prompt": "clear portrait of a superhero concept between spiderman and batman, cottagecore!!, background hyper detailed, character concept, full body, dynamic pose, intricate, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, art by artgerm and greg rutkowski and alphonse mucha", "scheduler": "K_EULER", "num_outputs": 1, "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run cjwbw/stable-diffusion-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cjwbw/stable-diffusion-v2:e5e1fd333a08c8035974a01dd42f799f1cca4625aec374643d716d9ae40cf2e4", { input: { width: 768, height: 768, prompt: "clear portrait of a superhero concept between spiderman and batman, cottagecore!!, background hyper detailed, character concept, full body, dynamic pose, intricate, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, art by artgerm and greg rutkowski and alphonse mucha", scheduler: "K_EULER", num_outputs: 1, guidance_scale: 7.5, prompt_strength: 0.8, num_inference_steps: 50 } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the client:import replicate
Run cjwbw/stable-diffusion-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cjwbw/stable-diffusion-v2:e5e1fd333a08c8035974a01dd42f799f1cca4625aec374643d716d9ae40cf2e4", input={ "width": 768, "height": 768, "prompt": "clear portrait of a superhero concept between spiderman and batman, cottagecore!!, background hyper detailed, character concept, full body, dynamic pose, intricate, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, art by artgerm and greg rutkowski and alphonse mucha", "scheduler": "K_EULER", "num_outputs": 1, "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run cjwbw/stable-diffusion-v2 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": "e5e1fd333a08c8035974a01dd42f799f1cca4625aec374643d716d9ae40cf2e4", "input": { "width": 768, "height": 768, "prompt": "clear portrait of a superhero concept between spiderman and batman, cottagecore!!, background hyper detailed, character concept, full body, dynamic pose, intricate, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, art by artgerm and greg rutkowski and alphonse mucha", "scheduler": "K_EULER", "num_outputs": 1, "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-11-24T20:28:10.630067Z", "created_at": "2022-11-24T20:28:03.269969Z", "data_removed": false, "error": null, "id": "cgtecb7rsncgdebsbiifkgfvtq", "input": { "width": 768, "height": 768, "prompt": "clear portrait of a superhero concept between spiderman and batman, cottagecore!!, background hyper detailed, character concept, full body, dynamic pose, intricate, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, art by artgerm and greg rutkowski and alphonse mucha", "scheduler": "K_EULER", "num_outputs": 1, "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 61271\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:07, 6.59it/s]\n 4%|▍ | 2/50 [00:00<00:06, 7.34it/s]\n 6%|▌ | 3/50 [00:00<00:06, 7.72it/s]\n 8%|▊ | 4/50 [00:00<00:05, 7.93it/s]\n 10%|█ | 5/50 [00:00<00:05, 8.06it/s]\n 12%|█▏ | 6/50 [00:00<00:05, 8.13it/s]\n 14%|█▍ | 7/50 [00:00<00:05, 8.18it/s]\n 16%|█▌ | 8/50 [00:01<00:05, 8.21it/s]\n 18%|█▊ | 9/50 [00:01<00:04, 8.23it/s]\n 20%|██ | 10/50 [00:01<00:04, 8.25it/s]\n 22%|██▏ | 11/50 [00:01<00:04, 8.25it/s]\n 24%|██▍ | 12/50 [00:01<00:04, 8.26it/s]\n 26%|██▌ | 13/50 [00:01<00:04, 8.27it/s]\n 28%|██▊ | 14/50 [00:01<00:04, 8.27it/s]\n 30%|███ | 15/50 [00:01<00:04, 8.27it/s]\n 32%|███▏ | 16/50 [00:01<00:04, 8.27it/s]\n 34%|███▍ | 17/50 [00:02<00:03, 8.27it/s]\n 36%|███▌ | 18/50 [00:02<00:03, 8.27it/s]\n 38%|███▊ | 19/50 [00:02<00:03, 8.28it/s]\n 40%|████ | 20/50 [00:02<00:03, 8.28it/s]\n 42%|████▏ | 21/50 [00:02<00:03, 8.28it/s]\n 44%|████▍ | 22/50 [00:02<00:03, 8.28it/s]\n 46%|████▌ | 23/50 [00:02<00:03, 8.28it/s]\n 48%|████▊ | 24/50 [00:02<00:03, 8.28it/s]\n 50%|█████ | 25/50 [00:03<00:03, 8.28it/s]\n 52%|█████▏ | 26/50 [00:03<00:02, 8.28it/s]\n 54%|█████▍ | 27/50 [00:03<00:02, 8.28it/s]\n 56%|█████▌ | 28/50 [00:03<00:02, 8.28it/s]\n 58%|█████▊ | 29/50 [00:03<00:02, 8.29it/s]\n 60%|██████ | 30/50 [00:03<00:02, 8.28it/s]\n 62%|██████▏ | 31/50 [00:03<00:02, 8.28it/s]\n 64%|██████▍ | 32/50 [00:03<00:02, 8.28it/s]\n 66%|██████▌ | 33/50 [00:04<00:02, 8.28it/s]\n 68%|██████▊ | 34/50 [00:04<00:01, 8.28it/s]\n 70%|███████ | 35/50 [00:04<00:01, 8.28it/s]\n 72%|███████▏ | 36/50 [00:04<00:01, 8.28it/s]\n 74%|███████▍ | 37/50 [00:04<00:01, 8.29it/s]\n 76%|███████▌ | 38/50 [00:04<00:01, 8.28it/s]\n 78%|███████▊ | 39/50 [00:04<00:01, 8.28it/s]\n 80%|████████ | 40/50 [00:04<00:01, 8.28it/s]\n 82%|████████▏ | 41/50 [00:04<00:01, 8.28it/s]\n 84%|████████▍ | 42/50 [00:05<00:00, 8.26it/s]\n 86%|████████▌ | 43/50 [00:05<00:00, 8.25it/s]\n 88%|████████▊ | 44/50 [00:05<00:00, 8.25it/s]\n 90%|█████████ | 45/50 [00:05<00:00, 8.25it/s]\n 92%|█████████▏| 46/50 [00:05<00:00, 8.26it/s]\n 94%|█████████▍| 47/50 [00:05<00:00, 8.27it/s]\n 96%|█████████▌| 48/50 [00:05<00:00, 8.27it/s]\n 98%|█████████▊| 49/50 [00:05<00:00, 8.27it/s]\n100%|██████████| 50/50 [00:06<00:00, 8.27it/s]\n100%|██████████| 50/50 [00:06<00:00, 8.23it/s]", "metrics": { "predict_time": 7.325471, "total_time": 7.360098 }, "output": [ "https://replicate.delivery/pbxt/EoGbSbEriBLEIBu0hgSC4UZrQqzzGypOIbL1FAJfIIeZXYDQA/out-0.png" ], "started_at": "2022-11-24T20:28:03.304596Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/cgtecb7rsncgdebsbiifkgfvtq", "cancel": "https://api.replicate.com/v1/predictions/cgtecb7rsncgdebsbiifkgfvtq/cancel" }, "version": "c30213da7590809923baf815fc42147f8aa15cf8d4396fb8d7e947cf9fdfad5f" }
Generated inUsing seed: 61271 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:07, 6.59it/s] 4%|▍ | 2/50 [00:00<00:06, 7.34it/s] 6%|▌ | 3/50 [00:00<00:06, 7.72it/s] 8%|▊ | 4/50 [00:00<00:05, 7.93it/s] 10%|█ | 5/50 [00:00<00:05, 8.06it/s] 12%|█▏ | 6/50 [00:00<00:05, 8.13it/s] 14%|█▍ | 7/50 [00:00<00:05, 8.18it/s] 16%|█▌ | 8/50 [00:01<00:05, 8.21it/s] 18%|█▊ | 9/50 [00:01<00:04, 8.23it/s] 20%|██ | 10/50 [00:01<00:04, 8.25it/s] 22%|██▏ | 11/50 [00:01<00:04, 8.25it/s] 24%|██▍ | 12/50 [00:01<00:04, 8.26it/s] 26%|██▌ | 13/50 [00:01<00:04, 8.27it/s] 28%|██▊ | 14/50 [00:01<00:04, 8.27it/s] 30%|███ | 15/50 [00:01<00:04, 8.27it/s] 32%|███▏ | 16/50 [00:01<00:04, 8.27it/s] 34%|███▍ | 17/50 [00:02<00:03, 8.27it/s] 36%|███▌ | 18/50 [00:02<00:03, 8.27it/s] 38%|███▊ | 19/50 [00:02<00:03, 8.28it/s] 40%|████ | 20/50 [00:02<00:03, 8.28it/s] 42%|████▏ | 21/50 [00:02<00:03, 8.28it/s] 44%|████▍ | 22/50 [00:02<00:03, 8.28it/s] 46%|████▌ | 23/50 [00:02<00:03, 8.28it/s] 48%|████▊ | 24/50 [00:02<00:03, 8.28it/s] 50%|█████ | 25/50 [00:03<00:03, 8.28it/s] 52%|█████▏ | 26/50 [00:03<00:02, 8.28it/s] 54%|█████▍ | 27/50 [00:03<00:02, 8.28it/s] 56%|█████▌ | 28/50 [00:03<00:02, 8.28it/s] 58%|█████▊ | 29/50 [00:03<00:02, 8.29it/s] 60%|██████ | 30/50 [00:03<00:02, 8.28it/s] 62%|██████▏ | 31/50 [00:03<00:02, 8.28it/s] 64%|██████▍ | 32/50 [00:03<00:02, 8.28it/s] 66%|██████▌ | 33/50 [00:04<00:02, 8.28it/s] 68%|██████▊ | 34/50 [00:04<00:01, 8.28it/s] 70%|███████ | 35/50 [00:04<00:01, 8.28it/s] 72%|███████▏ | 36/50 [00:04<00:01, 8.28it/s] 74%|███████▍ | 37/50 [00:04<00:01, 8.29it/s] 76%|███████▌ | 38/50 [00:04<00:01, 8.28it/s] 78%|███████▊ | 39/50 [00:04<00:01, 8.28it/s] 80%|████████ | 40/50 [00:04<00:01, 8.28it/s] 82%|████████▏ | 41/50 [00:04<00:01, 8.28it/s] 84%|████████▍ | 42/50 [00:05<00:00, 8.26it/s] 86%|████████▌ | 43/50 [00:05<00:00, 8.25it/s] 88%|████████▊ | 44/50 [00:05<00:00, 8.25it/s] 90%|█████████ | 45/50 [00:05<00:00, 8.25it/s] 92%|█████████▏| 46/50 [00:05<00:00, 8.26it/s] 94%|█████████▍| 47/50 [00:05<00:00, 8.27it/s] 96%|█████████▌| 48/50 [00:05<00:00, 8.27it/s] 98%|█████████▊| 49/50 [00:05<00:00, 8.27it/s] 100%|██████████| 50/50 [00:06<00:00, 8.27it/s] 100%|██████████| 50/50 [00:06<00:00, 8.23it/s]
Prediction
cjwbw/stable-diffusion-v2:e5e1fd33ID4kph3tu7gfgqxo4i7vomhw6r3iStatusSucceededSourceWebHardware–Total durationCreatedInput
- width
- 768
- height
- 768
- prompt
- beautiful open kitchen in the style of elena of avalor overlooking aerial wide angle view of a solarpunk vibrant city with greenery, interior architecture, kitchen, eating space, rendered in octane, in the style of Luc Schuiten, craig mullins, solarpunk in deviantart, photorealistic, highly detailed, Vincent Callebaut, elena of avalor, highly detailed
- scheduler
- K_EULER
- num_outputs
- "1"
- guidance_scale
- 7.5
- prompt_strength
- 0.8
- num_inference_steps
- "50"
{ "width": 768, "height": 768, "prompt": "beautiful open kitchen in the style of elena of avalor overlooking aerial wide angle view of a solarpunk vibrant city with greenery, interior architecture, kitchen, eating space, rendered in octane, in the style of Luc Schuiten, craig mullins, solarpunk in deviantart, photorealistic, highly detailed, Vincent Callebaut, elena of avalor, highly detailed", "scheduler": "K_EULER", "num_outputs": "1", "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": "50" }
Install Replicate’s Node.js client library:npm install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run cjwbw/stable-diffusion-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cjwbw/stable-diffusion-v2:e5e1fd333a08c8035974a01dd42f799f1cca4625aec374643d716d9ae40cf2e4", { input: { width: 768, height: 768, prompt: "beautiful open kitchen in the style of elena of avalor overlooking aerial wide angle view of a solarpunk vibrant city with greenery, interior architecture, kitchen, eating space, rendered in octane, in the style of Luc Schuiten, craig mullins, solarpunk in deviantart, photorealistic, highly detailed, Vincent Callebaut, elena of avalor, highly detailed", scheduler: "K_EULER", num_outputs: "1", guidance_scale: 7.5, prompt_strength: 0.8, num_inference_steps: "50" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the client:import replicate
Run cjwbw/stable-diffusion-v2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cjwbw/stable-diffusion-v2:e5e1fd333a08c8035974a01dd42f799f1cca4625aec374643d716d9ae40cf2e4", input={ "width": 768, "height": 768, "prompt": "beautiful open kitchen in the style of elena of avalor overlooking aerial wide angle view of a solarpunk vibrant city with greenery, interior architecture, kitchen, eating space, rendered in octane, in the style of Luc Schuiten, craig mullins, solarpunk in deviantart, photorealistic, highly detailed, Vincent Callebaut, elena of avalor, highly detailed", "scheduler": "K_EULER", "num_outputs": "1", "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": "50" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run cjwbw/stable-diffusion-v2 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": "e5e1fd333a08c8035974a01dd42f799f1cca4625aec374643d716d9ae40cf2e4", "input": { "width": 768, "height": 768, "prompt": "beautiful open kitchen in the style of elena of avalor overlooking aerial wide angle view of a solarpunk vibrant city with greenery, interior architecture, kitchen, eating space, rendered in octane, in the style of Luc Schuiten, craig mullins, solarpunk in deviantart, photorealistic, highly detailed, Vincent Callebaut, elena of avalor, highly detailed", "scheduler": "K_EULER", "num_outputs": "1", "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": "50" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2022-11-24T20:38:45.833746Z", "created_at": "2022-11-24T20:38:38.516381Z", "data_removed": false, "error": null, "id": "4kph3tu7gfgqxo4i7vomhw6r3i", "input": { "width": 768, "height": 768, "prompt": "beautiful open kitchen in the style of elena of avalor overlooking aerial wide angle view of a solarpunk vibrant city with greenery, interior architecture, kitchen, eating space, rendered in octane, in the style of Luc Schuiten, craig mullins, solarpunk in deviantart, photorealistic, highly detailed, Vincent Callebaut, elena of avalor, highly detailed", "scheduler": "K_EULER", "num_outputs": "1", "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": "50" }, "logs": "Using seed: 27891\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:07, 6.60it/s]\n 4%|▍ | 2/50 [00:00<00:06, 7.05it/s]\n 6%|▌ | 3/50 [00:00<00:06, 7.57it/s]\n 8%|▊ | 4/50 [00:00<00:05, 7.84it/s]\n 10%|█ | 5/50 [00:00<00:05, 8.00it/s]\n 12%|█▏ | 6/50 [00:00<00:05, 8.10it/s]\n 14%|█▍ | 7/50 [00:00<00:05, 8.17it/s]\n 16%|█▌ | 8/50 [00:01<00:05, 8.21it/s]\n 18%|█▊ | 9/50 [00:01<00:04, 8.24it/s]\n 20%|██ | 10/50 [00:01<00:04, 8.26it/s]\n 22%|██▏ | 11/50 [00:01<00:04, 8.27it/s]\n 24%|██▍ | 12/50 [00:01<00:04, 8.28it/s]\n 26%|██▌ | 13/50 [00:01<00:04, 8.29it/s]\n 28%|██▊ | 14/50 [00:01<00:04, 8.29it/s]\n 30%|███ | 15/50 [00:01<00:04, 8.29it/s]\n 32%|███▏ | 16/50 [00:01<00:04, 8.29it/s]\n 34%|███▍ | 17/50 [00:02<00:03, 8.29it/s]\n 36%|███▌ | 18/50 [00:02<00:03, 8.29it/s]\n 38%|███▊ | 19/50 [00:02<00:03, 8.29it/s]\n 40%|████ | 20/50 [00:02<00:03, 8.29it/s]\n 42%|████▏ | 21/50 [00:02<00:03, 8.29it/s]\n 44%|████▍ | 22/50 [00:02<00:03, 8.29it/s]\n 46%|████▌ | 23/50 [00:02<00:03, 8.29it/s]\n 48%|████▊ | 24/50 [00:02<00:03, 8.30it/s]\n 50%|█████ | 25/50 [00:03<00:03, 8.29it/s]\n 52%|█████▏ | 26/50 [00:03<00:02, 8.29it/s]\n 54%|█████▍ | 27/50 [00:03<00:02, 8.29it/s]\n 56%|█████▌ | 28/50 [00:03<00:02, 8.29it/s]\n 58%|█████▊ | 29/50 [00:03<00:02, 8.29it/s]\n 60%|██████ | 30/50 [00:03<00:02, 8.29it/s]\n 62%|██████▏ | 31/50 [00:03<00:02, 8.29it/s]\n 64%|██████▍ | 32/50 [00:03<00:02, 8.29it/s]\n 66%|██████▌ | 33/50 [00:04<00:02, 8.28it/s]\n 68%|██████▊ | 34/50 [00:04<00:01, 8.28it/s]\n 70%|███████ | 35/50 [00:04<00:01, 8.29it/s]\n 72%|███████▏ | 36/50 [00:04<00:01, 8.30it/s]\n 74%|███████▍ | 37/50 [00:04<00:01, 8.30it/s]\n 76%|███████▌ | 38/50 [00:04<00:01, 8.31it/s]\n 78%|███████▊ | 39/50 [00:04<00:01, 8.31it/s]\n 80%|████████ | 40/50 [00:04<00:01, 8.31it/s]\n 82%|████████▏ | 41/50 [00:04<00:01, 8.30it/s]\n 84%|████████▍ | 42/50 [00:05<00:00, 8.29it/s]\n 86%|████████▌ | 43/50 [00:05<00:00, 8.30it/s]\n 88%|████████▊ | 44/50 [00:05<00:00, 8.30it/s]\n 90%|█████████ | 45/50 [00:05<00:00, 8.30it/s]\n 92%|█████████▏| 46/50 [00:05<00:00, 8.30it/s]\n 94%|█████████▍| 47/50 [00:05<00:00, 8.30it/s]\n 96%|█████████▌| 48/50 [00:05<00:00, 8.30it/s]\n 98%|█████████▊| 49/50 [00:05<00:00, 8.31it/s]\n100%|██████████| 50/50 [00:06<00:00, 8.30it/s]\n100%|██████████| 50/50 [00:06<00:00, 8.23it/s]", "metrics": { "predict_time": 7.273606, "total_time": 7.317365 }, "output": [ "https://replicate.delivery/pbxt/bTqR1X42Ux50PRpd0HVbML8zLqz5oAV6H8JbvFYcmvYVI2AE/out-0.png" ], "started_at": "2022-11-24T20:38:38.560140Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/4kph3tu7gfgqxo4i7vomhw6r3i", "cancel": "https://api.replicate.com/v1/predictions/4kph3tu7gfgqxo4i7vomhw6r3i/cancel" }, "version": "c30213da7590809923baf815fc42147f8aa15cf8d4396fb8d7e947cf9fdfad5f" }
Generated inUsing seed: 27891 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:07, 6.60it/s] 4%|▍ | 2/50 [00:00<00:06, 7.05it/s] 6%|▌ | 3/50 [00:00<00:06, 7.57it/s] 8%|▊ | 4/50 [00:00<00:05, 7.84it/s] 10%|█ | 5/50 [00:00<00:05, 8.00it/s] 12%|█▏ | 6/50 [00:00<00:05, 8.10it/s] 14%|█▍ | 7/50 [00:00<00:05, 8.17it/s] 16%|█▌ | 8/50 [00:01<00:05, 8.21it/s] 18%|█▊ | 9/50 [00:01<00:04, 8.24it/s] 20%|██ | 10/50 [00:01<00:04, 8.26it/s] 22%|██▏ | 11/50 [00:01<00:04, 8.27it/s] 24%|██▍ | 12/50 [00:01<00:04, 8.28it/s] 26%|██▌ | 13/50 [00:01<00:04, 8.29it/s] 28%|██▊ | 14/50 [00:01<00:04, 8.29it/s] 30%|███ | 15/50 [00:01<00:04, 8.29it/s] 32%|███▏ | 16/50 [00:01<00:04, 8.29it/s] 34%|███▍ | 17/50 [00:02<00:03, 8.29it/s] 36%|███▌ | 18/50 [00:02<00:03, 8.29it/s] 38%|███▊ | 19/50 [00:02<00:03, 8.29it/s] 40%|████ | 20/50 [00:02<00:03, 8.29it/s] 42%|████▏ | 21/50 [00:02<00:03, 8.29it/s] 44%|████▍ | 22/50 [00:02<00:03, 8.29it/s] 46%|████▌ | 23/50 [00:02<00:03, 8.29it/s] 48%|████▊ | 24/50 [00:02<00:03, 8.30it/s] 50%|█████ | 25/50 [00:03<00:03, 8.29it/s] 52%|█████▏ | 26/50 [00:03<00:02, 8.29it/s] 54%|█████▍ | 27/50 [00:03<00:02, 8.29it/s] 56%|█████▌ | 28/50 [00:03<00:02, 8.29it/s] 58%|█████▊ | 29/50 [00:03<00:02, 8.29it/s] 60%|██████ | 30/50 [00:03<00:02, 8.29it/s] 62%|██████▏ | 31/50 [00:03<00:02, 8.29it/s] 64%|██████▍ | 32/50 [00:03<00:02, 8.29it/s] 66%|██████▌ | 33/50 [00:04<00:02, 8.28it/s] 68%|██████▊ | 34/50 [00:04<00:01, 8.28it/s] 70%|███████ | 35/50 [00:04<00:01, 8.29it/s] 72%|███████▏ | 36/50 [00:04<00:01, 8.30it/s] 74%|███████▍ | 37/50 [00:04<00:01, 8.30it/s] 76%|███████▌ | 38/50 [00:04<00:01, 8.31it/s] 78%|███████▊ | 39/50 [00:04<00:01, 8.31it/s] 80%|████████ | 40/50 [00:04<00:01, 8.31it/s] 82%|████████▏ | 41/50 [00:04<00:01, 8.30it/s] 84%|████████▍ | 42/50 [00:05<00:00, 8.29it/s] 86%|████████▌ | 43/50 [00:05<00:00, 8.30it/s] 88%|████████▊ | 44/50 [00:05<00:00, 8.30it/s] 90%|█████████ | 45/50 [00:05<00:00, 8.30it/s] 92%|█████████▏| 46/50 [00:05<00:00, 8.30it/s] 94%|█████████▍| 47/50 [00:05<00:00, 8.30it/s] 96%|█████████▌| 48/50 [00:05<00:00, 8.30it/s] 98%|█████████▊| 49/50 [00:05<00:00, 8.31it/s] 100%|██████████| 50/50 [00:06<00:00, 8.30it/s] 100%|██████████| 50/50 [00:06<00:00, 8.23it/s]
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