zsxkib
/
instant-id
Make realistic images of real people instantly
Prediction
zsxkib/instant-id:2e4785a4IDtzqpu7tbuxxeq4u2j7xrpwmymqStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 640
- height
- 640
- prompt
- 4k photo of a man. highly detailed, best quality, shallow depth of field, fuji film
- sdxl_weights
- stable-diffusion-xl-base-1.0
- guidance_scale
- 5
- negative_prompt
- ugly, (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured
- ip_adapter_scale
- 0.8
- num_inference_steps
- 30
- controlnet_conditioning_scale
- 0.8
{ "image": "https://replicate.delivery/pbxt/KI4a4NSCc0sAFMdlbD4n8ufHLXb2utKIwwbQff0M2ryhGJPJ/pp_0.jpg", "width": 640, "height": 640, "prompt": "4k photo of a man. highly detailed, best quality, shallow depth of field, fuji film", "sdxl_weights": "stable-diffusion-xl-base-1.0", "guidance_scale": 5, "negative_prompt": "ugly, (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured", "ip_adapter_scale": 0.8, "num_inference_steps": 30, "controlnet_conditioning_scale": 0.8 }
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 zsxkib/instant-id using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/instant-id:2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", { input: { image: "https://replicate.delivery/pbxt/KI4a4NSCc0sAFMdlbD4n8ufHLXb2utKIwwbQff0M2ryhGJPJ/pp_0.jpg", prompt: "4k photo of a man. highly detailed, best quality, shallow depth of field, fuji film", sdxl_weights: "stable-diffusion-xl-base-1.0", guidance_scale: 5, negative_prompt: "ugly, (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured", ip_adapter_scale: 0.8, num_inference_steps: 30, controlnet_conditioning_scale: 0.8 } } ); 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 zsxkib/instant-id using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/instant-id:2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", input={ "image": "https://replicate.delivery/pbxt/KI4a4NSCc0sAFMdlbD4n8ufHLXb2utKIwwbQff0M2ryhGJPJ/pp_0.jpg", "prompt": "4k photo of a man. highly detailed, best quality, shallow depth of field, fuji film", "sdxl_weights": "stable-diffusion-xl-base-1.0", "guidance_scale": 5, "negative_prompt": "ugly, (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured", "ip_adapter_scale": 0.8, "num_inference_steps": 30, "controlnet_conditioning_scale": 0.8 } ) 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 zsxkib/instant-id 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": "2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", "input": { "image": "https://replicate.delivery/pbxt/KI4a4NSCc0sAFMdlbD4n8ufHLXb2utKIwwbQff0M2ryhGJPJ/pp_0.jpg", "prompt": "4k photo of a man. highly detailed, best quality, shallow depth of field, fuji film", "sdxl_weights": "stable-diffusion-xl-base-1.0", "guidance_scale": 5, "negative_prompt": "ugly, (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured", "ip_adapter_scale": 0.8, "num_inference_steps": 30, "controlnet_conditioning_scale": 0.8 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-01-26T00:14:36.234677Z", "created_at": "2024-01-26T00:14:18.514716Z", "data_removed": false, "error": null, "id": "tzqpu7tbuxxeq4u2j7xrpwmymq", "input": { "image": "https://replicate.delivery/pbxt/KI4a4NSCc0sAFMdlbD4n8ufHLXb2utKIwwbQff0M2ryhGJPJ/pp_0.jpg", "width": 640, "height": 640, "prompt": "4k photo of a man. highly detailed, best quality, shallow depth of field, fuji film", "sdxl_weights": "stable-diffusion-xl-base-1.0", "guidance_scale": 5, "negative_prompt": "ugly, (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured", "ip_adapter_scale": 0.8, "num_inference_steps": 30, "controlnet_conditioning_scale": 0.8 }, "logs": "0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:10, 2.79it/s]\n 7%|▋ | 2/30 [00:00<00:09, 2.89it/s]\n 10%|█ | 3/30 [00:01<00:09, 2.92it/s]\n 13%|█▎ | 4/30 [00:01<00:08, 2.94it/s]\n 17%|█▋ | 5/30 [00:01<00:08, 2.95it/s]\n 20%|██ | 6/30 [00:02<00:08, 2.95it/s]\n 23%|██▎ | 7/30 [00:02<00:07, 2.96it/s]\n 27%|██▋ | 8/30 [00:02<00:07, 2.96it/s]\n 30%|███ | 9/30 [00:03<00:07, 2.96it/s]\n 33%|███▎ | 10/30 [00:03<00:06, 2.96it/s]\n 37%|███▋ | 11/30 [00:03<00:06, 2.96it/s]\n 40%|████ | 12/30 [00:04<00:06, 2.95it/s]\n 43%|████▎ | 13/30 [00:04<00:05, 2.96it/s]\n 47%|████▋ | 14/30 [00:04<00:05, 2.96it/s]\n 50%|█████ | 15/30 [00:05<00:05, 2.96it/s]\n 53%|█████▎ | 16/30 [00:05<00:04, 2.96it/s]\n 57%|█████▋ | 17/30 [00:05<00:04, 2.96it/s]\n 60%|██████ | 18/30 [00:06<00:04, 2.95it/s]\n 63%|██████▎ | 19/30 [00:06<00:03, 2.95it/s]\n 67%|██████▋ | 20/30 [00:06<00:03, 2.96it/s]\n 70%|███████ | 21/30 [00:07<00:03, 2.97it/s]\n 73%|███████▎ | 22/30 [00:07<00:02, 2.97it/s]\n 77%|███████▋ | 23/30 [00:07<00:02, 2.97it/s]\n 80%|████████ | 24/30 [00:08<00:02, 2.97it/s]\n 83%|████████▎ | 25/30 [00:08<00:01, 2.97it/s]\n 87%|████████▋ | 26/30 [00:08<00:01, 2.97it/s]\n 90%|█████████ | 27/30 [00:09<00:01, 2.97it/s]\n 93%|█████████▎| 28/30 [00:09<00:00, 2.96it/s]\n 97%|█████████▋| 29/30 [00:09<00:00, 2.96it/s]\n100%|██████████| 30/30 [00:10<00:00, 2.97it/s]\n100%|██████████| 30/30 [00:10<00:00, 2.96it/s]", "metrics": { "predict_time": 17.633786, "total_time": 17.719961 }, "output": "https://replicate.delivery/pbxt/Wnbjkn351EbjOBTZi4a8RR0MQ7KJyxSG7K32NefeHbrXbVgkA/result.jpg", "started_at": "2024-01-26T00:14:18.600891Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/tzqpu7tbuxxeq4u2j7xrpwmymq", "cancel": "https://api.replicate.com/v1/predictions/tzqpu7tbuxxeq4u2j7xrpwmymq/cancel" }, "version": "4a86d2bcb78e94f5fcda66492b1acdf8781b252fbe55714fb67b30e66c4512f4" }
Generated in0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:10, 2.79it/s] 7%|▋ | 2/30 [00:00<00:09, 2.89it/s] 10%|█ | 3/30 [00:01<00:09, 2.92it/s] 13%|█▎ | 4/30 [00:01<00:08, 2.94it/s] 17%|█▋ | 5/30 [00:01<00:08, 2.95it/s] 20%|██ | 6/30 [00:02<00:08, 2.95it/s] 23%|██▎ | 7/30 [00:02<00:07, 2.96it/s] 27%|██▋ | 8/30 [00:02<00:07, 2.96it/s] 30%|███ | 9/30 [00:03<00:07, 2.96it/s] 33%|███▎ | 10/30 [00:03<00:06, 2.96it/s] 37%|███▋ | 11/30 [00:03<00:06, 2.96it/s] 40%|████ | 12/30 [00:04<00:06, 2.95it/s] 43%|████▎ | 13/30 [00:04<00:05, 2.96it/s] 47%|████▋ | 14/30 [00:04<00:05, 2.96it/s] 50%|█████ | 15/30 [00:05<00:05, 2.96it/s] 53%|█████▎ | 16/30 [00:05<00:04, 2.96it/s] 57%|█████▋ | 17/30 [00:05<00:04, 2.96it/s] 60%|██████ | 18/30 [00:06<00:04, 2.95it/s] 63%|██████▎ | 19/30 [00:06<00:03, 2.95it/s] 67%|██████▋ | 20/30 [00:06<00:03, 2.96it/s] 70%|███████ | 21/30 [00:07<00:03, 2.97it/s] 73%|███████▎ | 22/30 [00:07<00:02, 2.97it/s] 77%|███████▋ | 23/30 [00:07<00:02, 2.97it/s] 80%|████████ | 24/30 [00:08<00:02, 2.97it/s] 83%|████████▎ | 25/30 [00:08<00:01, 2.97it/s] 87%|████████▋ | 26/30 [00:08<00:01, 2.97it/s] 90%|█████████ | 27/30 [00:09<00:01, 2.97it/s] 93%|█████████▎| 28/30 [00:09<00:00, 2.96it/s] 97%|█████████▋| 29/30 [00:09<00:00, 2.96it/s] 100%|██████████| 30/30 [00:10<00:00, 2.97it/s] 100%|██████████| 30/30 [00:10<00:00, 2.96it/s]
Prediction
zsxkib/instant-id:2e4785a4IDh3yimr3bw62kvyvup3jg7j6s5yStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 640
- height
- 640
- prompt
- minimalist, very intricate colours, simplified continuous line colour drawing in the style of ink pen drawing by Michelangelo, white background, colours, heavy use of palette knives, only inky real colours on paper (colours)
- guidance_scale
- 5
- negative_prompt
- (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured, plain
- ip_adapter_scale
- 0.8
- num_inference_steps
- 30
- controlnet_conditioning_scale
- 0.8
{ "image": "https://replicate.delivery/pbxt/KGyS43owe6zh6PpqA2BDoIbPrFy6ef2BOEHvi4nuj5yE2VSq/yann-lecun_resize.jpg", "width": 640, "height": 640, "prompt": "minimalist, very intricate colours, simplified continuous line colour drawing in the style of ink pen drawing by Michelangelo, white background, colours, heavy use of palette knives, only inky real colours on paper (colours)", "guidance_scale": 5, "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured, plain", "ip_adapter_scale": 0.8, "num_inference_steps": 30, "controlnet_conditioning_scale": 0.8 }
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 zsxkib/instant-id using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/instant-id:2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", { input: { image: "https://replicate.delivery/pbxt/KGyS43owe6zh6PpqA2BDoIbPrFy6ef2BOEHvi4nuj5yE2VSq/yann-lecun_resize.jpg", prompt: "minimalist, very intricate colours, simplified continuous line colour drawing in the style of ink pen drawing by Michelangelo, white background, colours, heavy use of palette knives, only inky real colours on paper (colours)", guidance_scale: 5, negative_prompt: "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured, plain", ip_adapter_scale: 0.8, num_inference_steps: 30, controlnet_conditioning_scale: 0.8 } } ); 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 zsxkib/instant-id using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/instant-id:2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", input={ "image": "https://replicate.delivery/pbxt/KGyS43owe6zh6PpqA2BDoIbPrFy6ef2BOEHvi4nuj5yE2VSq/yann-lecun_resize.jpg", "prompt": "minimalist, very intricate colours, simplified continuous line colour drawing in the style of ink pen drawing by Michelangelo, white background, colours, heavy use of palette knives, only inky real colours on paper (colours)", "guidance_scale": 5, "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured, plain", "ip_adapter_scale": 0.8, "num_inference_steps": 30, "controlnet_conditioning_scale": 0.8 } ) 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 zsxkib/instant-id 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": "2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", "input": { "image": "https://replicate.delivery/pbxt/KGyS43owe6zh6PpqA2BDoIbPrFy6ef2BOEHvi4nuj5yE2VSq/yann-lecun_resize.jpg", "prompt": "minimalist, very intricate colours, simplified continuous line colour drawing in the style of ink pen drawing by Michelangelo, white background, colours, heavy use of palette knives, only inky real colours on paper (colours)", "guidance_scale": 5, "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured, plain", "ip_adapter_scale": 0.8, "num_inference_steps": 30, "controlnet_conditioning_scale": 0.8 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-01-22T21:56:52.342604Z", "created_at": "2024-01-22T21:56:25.196973Z", "data_removed": false, "error": null, "id": "h3yimr3bw62kvyvup3jg7j6s5y", "input": { "image": "https://replicate.delivery/pbxt/KGyS43owe6zh6PpqA2BDoIbPrFy6ef2BOEHvi4nuj5yE2VSq/yann-lecun_resize.jpg", "width": 640, "height": 640, "prompt": "minimalist, very intricate colours, simplified continuous line colour drawing in the style of ink pen drawing by Michelangelo, white background, colours, heavy use of palette knives, only inky real colours on paper (colours)", "guidance_scale": 5, "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured, plain", "ip_adapter_scale": 0.8, "num_inference_steps": 30, "controlnet_conditioning_scale": 0.8 }, "logs": "0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:19, 1.47it/s]\n 7%|▋ | 2/30 [00:01<00:19, 1.47it/s]\n 10%|█ | 3/30 [00:02<00:18, 1.47it/s]\n 13%|█▎ | 4/30 [00:02<00:17, 1.47it/s]\n 17%|█▋ | 5/30 [00:03<00:16, 1.47it/s]\n 20%|██ | 6/30 [00:04<00:16, 1.47it/s]\n 23%|██▎ | 7/30 [00:04<00:15, 1.47it/s]\n 27%|██▋ | 8/30 [00:05<00:14, 1.47it/s]\n 30%|███ | 9/30 [00:06<00:14, 1.47it/s]\n 33%|███▎ | 10/30 [00:06<00:13, 1.47it/s]\n 37%|███▋ | 11/30 [00:07<00:12, 1.47it/s]\n 40%|████ | 12/30 [00:08<00:12, 1.47it/s]\n 43%|████▎ | 13/30 [00:08<00:11, 1.47it/s]\n 47%|████▋ | 14/30 [00:09<00:10, 1.47it/s]\n 50%|█████ | 15/30 [00:10<00:10, 1.47it/s]\n 53%|█████▎ | 16/30 [00:10<00:09, 1.47it/s]\n 57%|█████▋ | 17/30 [00:11<00:08, 1.47it/s]\n 60%|██████ | 18/30 [00:12<00:08, 1.47it/s]\n 63%|██████▎ | 19/30 [00:12<00:07, 1.47it/s]\n 67%|██████▋ | 20/30 [00:13<00:06, 1.47it/s]\n 70%|███████ | 21/30 [00:14<00:06, 1.47it/s]\n 73%|███████▎ | 22/30 [00:14<00:05, 1.46it/s]\n 77%|███████▋ | 23/30 [00:15<00:04, 1.46it/s]\n 80%|████████ | 24/30 [00:16<00:04, 1.46it/s]\n 83%|████████▎ | 25/30 [00:17<00:03, 1.46it/s]\n 87%|████████▋ | 26/30 [00:17<00:02, 1.46it/s]\n 90%|█████████ | 27/30 [00:18<00:02, 1.46it/s]\n 93%|█████████▎| 28/30 [00:19<00:01, 1.46it/s]\n 97%|█████████▋| 29/30 [00:19<00:00, 1.46it/s]\n100%|██████████| 30/30 [00:20<00:00, 1.46it/s]\n100%|██████████| 30/30 [00:20<00:00, 1.47it/s]", "metrics": { "predict_time": 27.09831, "total_time": 27.145631 }, "output": "https://replicate.delivery/pbxt/k1c4UVXlTR5aDRMTSUQXQQcCKryKAWhkqMArBU3etQ1RtkHJA/result.jpg", "started_at": "2024-01-22T21:56:25.244294Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/h3yimr3bw62kvyvup3jg7j6s5y", "cancel": "https://api.replicate.com/v1/predictions/h3yimr3bw62kvyvup3jg7j6s5y/cancel" }, "version": "965db2664428311c75f49036a8ff261e1972ac714efd7d7a1c15c808db021b0e" }
Generated in0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:19, 1.47it/s] 7%|▋ | 2/30 [00:01<00:19, 1.47it/s] 10%|█ | 3/30 [00:02<00:18, 1.47it/s] 13%|█▎ | 4/30 [00:02<00:17, 1.47it/s] 17%|█▋ | 5/30 [00:03<00:16, 1.47it/s] 20%|██ | 6/30 [00:04<00:16, 1.47it/s] 23%|██▎ | 7/30 [00:04<00:15, 1.47it/s] 27%|██▋ | 8/30 [00:05<00:14, 1.47it/s] 30%|███ | 9/30 [00:06<00:14, 1.47it/s] 33%|███▎ | 10/30 [00:06<00:13, 1.47it/s] 37%|███▋ | 11/30 [00:07<00:12, 1.47it/s] 40%|████ | 12/30 [00:08<00:12, 1.47it/s] 43%|████▎ | 13/30 [00:08<00:11, 1.47it/s] 47%|████▋ | 14/30 [00:09<00:10, 1.47it/s] 50%|█████ | 15/30 [00:10<00:10, 1.47it/s] 53%|█████▎ | 16/30 [00:10<00:09, 1.47it/s] 57%|█████▋ | 17/30 [00:11<00:08, 1.47it/s] 60%|██████ | 18/30 [00:12<00:08, 1.47it/s] 63%|██████▎ | 19/30 [00:12<00:07, 1.47it/s] 67%|██████▋ | 20/30 [00:13<00:06, 1.47it/s] 70%|███████ | 21/30 [00:14<00:06, 1.47it/s] 73%|███████▎ | 22/30 [00:14<00:05, 1.46it/s] 77%|███████▋ | 23/30 [00:15<00:04, 1.46it/s] 80%|████████ | 24/30 [00:16<00:04, 1.46it/s] 83%|████████▎ | 25/30 [00:17<00:03, 1.46it/s] 87%|████████▋ | 26/30 [00:17<00:02, 1.46it/s] 90%|█████████ | 27/30 [00:18<00:02, 1.46it/s] 93%|█████████▎| 28/30 [00:19<00:01, 1.46it/s] 97%|█████████▋| 29/30 [00:19<00:00, 1.46it/s] 100%|██████████| 30/30 [00:20<00:00, 1.46it/s] 100%|██████████| 30/30 [00:20<00:00, 1.47it/s]
Prediction
zsxkib/instant-id:2e4785a4IDvlug6udbjej7rxaci6wi4z77nuStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 640
- height
- 640
- prompt
- A photo of a scientist img receiving the Nobel Prize
- guidance_scale
- 5
- negative_prompt
- nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry
- ip_adapter_scale
- 0.8
- num_inference_steps
- 30
- controlnet_conditioning_scale
- 0.8
{ "image": "https://replicate.delivery/pbxt/KGyAY0lYJT1bZezD3QXG7tcDaa99wfrJcxA4BNKi3kUpjPbe/sam_resize.png", "width": 640, "height": 640, "prompt": "A photo of a scientist img receiving the Nobel Prize", "guidance_scale": 5, "negative_prompt": "nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry", "ip_adapter_scale": 0.8, "num_inference_steps": 30, "controlnet_conditioning_scale": 0.8 }
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 zsxkib/instant-id using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/instant-id:2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", { input: { image: "https://replicate.delivery/pbxt/KGyAY0lYJT1bZezD3QXG7tcDaa99wfrJcxA4BNKi3kUpjPbe/sam_resize.png", prompt: "A photo of a scientist img receiving the Nobel Prize", guidance_scale: 5, negative_prompt: "nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry", ip_adapter_scale: 0.8, num_inference_steps: 30, controlnet_conditioning_scale: 0.8 } } ); 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 zsxkib/instant-id using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/instant-id:2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", input={ "image": "https://replicate.delivery/pbxt/KGyAY0lYJT1bZezD3QXG7tcDaa99wfrJcxA4BNKi3kUpjPbe/sam_resize.png", "prompt": "A photo of a scientist img receiving the Nobel Prize", "guidance_scale": 5, "negative_prompt": "nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry", "ip_adapter_scale": 0.8, "num_inference_steps": 30, "controlnet_conditioning_scale": 0.8 } ) 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 zsxkib/instant-id 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": "2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", "input": { "image": "https://replicate.delivery/pbxt/KGyAY0lYJT1bZezD3QXG7tcDaa99wfrJcxA4BNKi3kUpjPbe/sam_resize.png", "prompt": "A photo of a scientist img receiving the Nobel Prize", "guidance_scale": 5, "negative_prompt": "nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry", "ip_adapter_scale": 0.8, "num_inference_steps": 30, "controlnet_conditioning_scale": 0.8 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-01-22T22:01:33.655957Z", "created_at": "2024-01-22T22:01:04.969963Z", "data_removed": false, "error": null, "id": "vlug6udbjej7rxaci6wi4z77nu", "input": { "image": "https://replicate.delivery/pbxt/KGyAY0lYJT1bZezD3QXG7tcDaa99wfrJcxA4BNKi3kUpjPbe/sam_resize.png", "width": 640, "height": 640, "prompt": "A photo of a scientist img receiving the Nobel Prize", "guidance_scale": 5, "negative_prompt": "nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry", "ip_adapter_scale": 0.8, "num_inference_steps": 30, "controlnet_conditioning_scale": 0.8 }, "logs": "0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:19, 1.47it/s]\n 7%|▋ | 2/30 [00:01<00:19, 1.47it/s]\n 10%|█ | 3/30 [00:02<00:18, 1.47it/s]\n 13%|█▎ | 4/30 [00:02<00:17, 1.47it/s]\n 17%|█▋ | 5/30 [00:03<00:16, 1.47it/s]\n 20%|██ | 6/30 [00:04<00:16, 1.47it/s]\n 23%|██▎ | 7/30 [00:04<00:15, 1.47it/s]\n 27%|██▋ | 8/30 [00:05<00:14, 1.47it/s]\n 30%|███ | 9/30 [00:06<00:14, 1.47it/s]\n 33%|███▎ | 10/30 [00:06<00:13, 1.47it/s]\n 37%|███▋ | 11/30 [00:07<00:12, 1.47it/s]\n 40%|████ | 12/30 [00:08<00:12, 1.47it/s]\n 43%|████▎ | 13/30 [00:08<00:11, 1.47it/s]\n 47%|████▋ | 14/30 [00:09<00:10, 1.47it/s]\n 50%|█████ | 15/30 [00:10<00:10, 1.47it/s]\n 53%|█████▎ | 16/30 [00:10<00:09, 1.47it/s]\n 57%|█████▋ | 17/30 [00:11<00:08, 1.47it/s]\n 60%|██████ | 18/30 [00:12<00:08, 1.47it/s]\n 63%|██████▎ | 19/30 [00:12<00:07, 1.47it/s]\n 67%|██████▋ | 20/30 [00:13<00:06, 1.47it/s]\n 70%|███████ | 21/30 [00:14<00:06, 1.47it/s]\n 73%|███████▎ | 22/30 [00:14<00:05, 1.47it/s]\n 77%|███████▋ | 23/30 [00:15<00:04, 1.47it/s]\n 80%|████████ | 24/30 [00:16<00:04, 1.47it/s]\n 83%|████████▎ | 25/30 [00:17<00:03, 1.47it/s]\n 87%|████████▋ | 26/30 [00:17<00:02, 1.47it/s]\n 90%|█████████ | 27/30 [00:18<00:02, 1.47it/s]\n 93%|█████████▎| 28/30 [00:19<00:01, 1.47it/s]\n 97%|█████████▋| 29/30 [00:19<00:00, 1.47it/s]\n100%|██████████| 30/30 [00:20<00:00, 1.46it/s]\n100%|██████████| 30/30 [00:20<00:00, 1.47it/s]", "metrics": { "predict_time": 27.176196, "total_time": 28.685994 }, "output": "https://replicate.delivery/pbxt/m2ssM2QxTr6oPdcvoFnMebtNgDisWXPxIFH9r4fgWOe59SeIB/result.jpg", "started_at": "2024-01-22T22:01:06.479761Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/vlug6udbjej7rxaci6wi4z77nu", "cancel": "https://api.replicate.com/v1/predictions/vlug6udbjej7rxaci6wi4z77nu/cancel" }, "version": "965db2664428311c75f49036a8ff261e1972ac714efd7d7a1c15c808db021b0e" }
Generated in0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:19, 1.47it/s] 7%|▋ | 2/30 [00:01<00:19, 1.47it/s] 10%|█ | 3/30 [00:02<00:18, 1.47it/s] 13%|█▎ | 4/30 [00:02<00:17, 1.47it/s] 17%|█▋ | 5/30 [00:03<00:16, 1.47it/s] 20%|██ | 6/30 [00:04<00:16, 1.47it/s] 23%|██▎ | 7/30 [00:04<00:15, 1.47it/s] 27%|██▋ | 8/30 [00:05<00:14, 1.47it/s] 30%|███ | 9/30 [00:06<00:14, 1.47it/s] 33%|███▎ | 10/30 [00:06<00:13, 1.47it/s] 37%|███▋ | 11/30 [00:07<00:12, 1.47it/s] 40%|████ | 12/30 [00:08<00:12, 1.47it/s] 43%|████▎ | 13/30 [00:08<00:11, 1.47it/s] 47%|████▋ | 14/30 [00:09<00:10, 1.47it/s] 50%|█████ | 15/30 [00:10<00:10, 1.47it/s] 53%|█████▎ | 16/30 [00:10<00:09, 1.47it/s] 57%|█████▋ | 17/30 [00:11<00:08, 1.47it/s] 60%|██████ | 18/30 [00:12<00:08, 1.47it/s] 63%|██████▎ | 19/30 [00:12<00:07, 1.47it/s] 67%|██████▋ | 20/30 [00:13<00:06, 1.47it/s] 70%|███████ | 21/30 [00:14<00:06, 1.47it/s] 73%|███████▎ | 22/30 [00:14<00:05, 1.47it/s] 77%|███████▋ | 23/30 [00:15<00:04, 1.47it/s] 80%|████████ | 24/30 [00:16<00:04, 1.47it/s] 83%|████████▎ | 25/30 [00:17<00:03, 1.47it/s] 87%|████████▋ | 26/30 [00:17<00:02, 1.47it/s] 90%|█████████ | 27/30 [00:18<00:02, 1.47it/s] 93%|█████████▎| 28/30 [00:19<00:01, 1.47it/s] 97%|█████████▋| 29/30 [00:19<00:00, 1.47it/s] 100%|██████████| 30/30 [00:20<00:00, 1.46it/s] 100%|██████████| 30/30 [00:20<00:00, 1.47it/s]
Prediction
zsxkib/instant-id:2e4785a4IDr766fk3ban74fwagxopi7mqsxeStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 640
- height
- 640
- prompt
- masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished
- scheduler
- EulerDiscreteScheduler
- enable_lcm
- sdxl_weights
- nightvision-xl-0791
- pose_strength
- 0.4
- canny_strength
- 0.3
- depth_strength
- 0.5
- guidance_scale
- 5
- negative_prompt
- (lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green
- ip_adapter_scale
- 0.8
- lcm_guidance_scale
- 1.5
- num_inference_steps
- 30
- enable_pose_controlnet
- enhance_nonface_region
- enable_canny_controlnet
- enable_depth_controlnet
- lcm_num_inference_steps
- 5
- controlnet_conditioning_scale
- 0.8
{ "image": "https://replicate.delivery/pbxt/KMB8vhqlXLdAcElPz8lcQhtJrzzOzJEsdwWfkXAyuhotbKwq/meisje_met_de_parel.webp", "width": 640, "height": 640, "prompt": "masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished", "scheduler": "EulerDiscreteScheduler", "enable_lcm": false, "sdxl_weights": "nightvision-xl-0791", "pose_strength": 0.4, "canny_strength": 0.3, "depth_strength": 0.5, "guidance_scale": 5, "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green", "ip_adapter_scale": 0.8, "lcm_guidance_scale": 1.5, "num_inference_steps": 30, "enable_pose_controlnet": true, "enhance_nonface_region": true, "enable_canny_controlnet": true, "enable_depth_controlnet": false, "lcm_num_inference_steps": 5, "controlnet_conditioning_scale": 0.8 }
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 zsxkib/instant-id using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/instant-id:2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", { input: { image: "https://replicate.delivery/pbxt/KMB8vhqlXLdAcElPz8lcQhtJrzzOzJEsdwWfkXAyuhotbKwq/meisje_met_de_parel.webp", prompt: "masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished", scheduler: "EulerDiscreteScheduler", enable_lcm: false, sdxl_weights: "nightvision-xl-0791", pose_strength: 0.4, canny_strength: 0.3, depth_strength: 0.5, guidance_scale: 5, negative_prompt: "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green", ip_adapter_scale: 0.8, lcm_guidance_scale: 1.5, num_inference_steps: 30, enable_pose_controlnet: true, enhance_nonface_region: true, enable_canny_controlnet: true, enable_depth_controlnet: false, lcm_num_inference_steps: 5, controlnet_conditioning_scale: 0.8 } } ); 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 zsxkib/instant-id using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/instant-id:2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", input={ "image": "https://replicate.delivery/pbxt/KMB8vhqlXLdAcElPz8lcQhtJrzzOzJEsdwWfkXAyuhotbKwq/meisje_met_de_parel.webp", "prompt": "masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished", "scheduler": "EulerDiscreteScheduler", "enable_lcm": False, "sdxl_weights": "nightvision-xl-0791", "pose_strength": 0.4, "canny_strength": 0.3, "depth_strength": 0.5, "guidance_scale": 5, "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green", "ip_adapter_scale": 0.8, "lcm_guidance_scale": 1.5, "num_inference_steps": 30, "enable_pose_controlnet": True, "enhance_nonface_region": True, "enable_canny_controlnet": True, "enable_depth_controlnet": False, "lcm_num_inference_steps": 5, "controlnet_conditioning_scale": 0.8 } ) 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 zsxkib/instant-id 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": "2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", "input": { "image": "https://replicate.delivery/pbxt/KMB8vhqlXLdAcElPz8lcQhtJrzzOzJEsdwWfkXAyuhotbKwq/meisje_met_de_parel.webp", "prompt": "masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished", "scheduler": "EulerDiscreteScheduler", "enable_lcm": false, "sdxl_weights": "nightvision-xl-0791", "pose_strength": 0.4, "canny_strength": 0.3, "depth_strength": 0.5, "guidance_scale": 5, "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green", "ip_adapter_scale": 0.8, "lcm_guidance_scale": 1.5, "num_inference_steps": 30, "enable_pose_controlnet": true, "enhance_nonface_region": true, "enable_canny_controlnet": true, "enable_depth_controlnet": false, "lcm_num_inference_steps": 5, "controlnet_conditioning_scale": 0.8 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-02-06T14:05:12.172734Z", "created_at": "2024-02-06T14:04:25.076266Z", "data_removed": false, "error": null, "id": "r766fk3ban74fwagxopi7mqsxe", "input": { "image": "https://replicate.delivery/pbxt/KMB8vhqlXLdAcElPz8lcQhtJrzzOzJEsdwWfkXAyuhotbKwq/meisje_met_de_parel.webp", "width": 640, "height": 640, "prompt": "masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished", "scheduler": "EulerDiscreteScheduler", "enable_lcm": false, "sdxl_weights": "nightvision-xl-0791", "pose_strength": 0.4, "canny_strength": 0.3, "depth_strength": 0.5, "guidance_scale": 5, "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green", "ip_adapter_scale": 0.8, "lcm_guidance_scale": 1.5, "num_inference_steps": 30, "enable_pose_controlnet": true, "enhance_nonface_region": true, "enable_canny_controlnet": true, "enable_depth_controlnet": false, "lcm_num_inference_steps": 5, "controlnet_conditioning_scale": 0.8 }, "logs": "Using seed: 31094\ndownloading url: https://weights.replicate.delivery/default/InstantID/models--stablediffusionapi--nightvision-xl-0791.tar\ndownloading to: checkpoints/models--stablediffusionapi--nightvision-xl-0791\n2024-02-06T14:04:25Z | INFO | [ Initiating ] dest=checkpoints/models--stablediffusionapi--nightvision-xl-0791 minimum_chunk_size=150M url=https://weights.replicate.delivery/default/InstantID/models--stablediffusionapi--nightvision-xl-0791.tar\n2024-02-06T14:04:33Z | INFO | [ Complete ] dest=checkpoints/models--stablediffusionapi--nightvision-xl-0791 size=\"6.9 GB\" total_elapsed=8.690s url=https://weights.replicate.delivery/default/InstantID/models--stablediffusionapi--nightvision-xl-0791.tar\ndownloading took: 9.307956218719482\n[~] Loading new SDXL weights: checkpoints/models--stablediffusionapi--nightvision-xl-0791/\nKeyword arguments {'safety_checker': None} are not expected by StableDiffusionXLInstantIDPipeline and will be ignored.\nLoading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]\nLoading pipeline components...: 14%|█▍ | 1/7 [00:00<00:02, 2.25it/s]\nLoading pipeline components...: 43%|████▎ | 3/7 [00:00<00:00, 5.65it/s]\nLoading pipeline components...: 57%|█████▋ | 4/7 [00:00<00:00, 4.84it/s]\nLoading pipeline components...: 86%|████████▌ | 6/7 [00:02<00:00, 1.65it/s]\nLoading pipeline components...: 100%|██████████| 7/7 [00:02<00:00, 2.42it/s]\n[~] Seting up LCM (just in case)\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/insightface/utils/transform.py:68: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.\nTo use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.\nP = np.linalg.lstsq(X_homo, Y)[0].T # Affine matrix. 3 x 4\nStart inference...\n[Debug] Prompt: masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished,\n[Debug] Neg Prompt: (lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:16, 1.79it/s]\n 7%|▋ | 2/30 [00:01<00:15, 1.79it/s]\n 10%|█ | 3/30 [00:01<00:15, 1.79it/s]\n 13%|█▎ | 4/30 [00:02<00:14, 1.78it/s]\n 17%|█▋ | 5/30 [00:02<00:14, 1.78it/s]\n 20%|██ | 6/30 [00:03<00:13, 1.78it/s]\n 23%|██▎ | 7/30 [00:03<00:12, 1.78it/s]\n 27%|██▋ | 8/30 [00:04<00:12, 1.78it/s]\n 30%|███ | 9/30 [00:05<00:11, 1.78it/s]\n 33%|███▎ | 10/30 [00:05<00:11, 1.77it/s]\n 37%|███▋ | 11/30 [00:06<00:10, 1.77it/s]\n 40%|████ | 12/30 [00:06<00:10, 1.77it/s]\n 43%|████▎ | 13/30 [00:07<00:09, 1.77it/s]\n 47%|████▋ | 14/30 [00:07<00:09, 1.77it/s]\n 50%|█████ | 15/30 [00:08<00:08, 1.77it/s]\n 53%|█████▎ | 16/30 [00:09<00:07, 1.77it/s]\n 57%|█████▋ | 17/30 [00:09<00:07, 1.77it/s]\n 60%|██████ | 18/30 [00:10<00:06, 1.77it/s]\n 63%|██████▎ | 19/30 [00:10<00:06, 1.77it/s]\n 67%|██████▋ | 20/30 [00:11<00:05, 1.77it/s]\n 70%|███████ | 21/30 [00:11<00:05, 1.77it/s]\n 73%|███████▎ | 22/30 [00:12<00:04, 1.77it/s]\n 77%|███████▋ | 23/30 [00:12<00:03, 1.77it/s]\n 80%|████████ | 24/30 [00:13<00:03, 1.77it/s]\n 83%|████████▎ | 25/30 [00:14<00:02, 1.77it/s]\n 87%|████████▋ | 26/30 [00:14<00:02, 1.77it/s]\n 90%|█████████ | 27/30 [00:15<00:01, 1.77it/s]\n 93%|█████████▎| 28/30 [00:15<00:01, 1.77it/s]\n 97%|█████████▋| 29/30 [00:16<00:00, 1.77it/s]\n100%|██████████| 30/30 [00:16<00:00, 1.77it/s]\n100%|██████████| 30/30 [00:16<00:00, 1.77it/s]\nNSFW content detected: False", "metrics": { "predict_time": 47.065249, "total_time": 47.096468 }, "output": [ "https://replicate.delivery/pbxt/AhtyoJfezztMUEvhkEXKKdeefqHLLqGF3emHkL7fQdIXLdfTSA/out_0.png" ], "started_at": "2024-02-06T14:04:25.107485Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/r766fk3ban74fwagxopi7mqsxe", "cancel": "https://api.replicate.com/v1/predictions/r766fk3ban74fwagxopi7mqsxe/cancel" }, "version": "6af8583c541261472e92155d87bba80d5ad98461665802f2ba196ac099aaedc9" }
Generated inUsing seed: 31094 downloading url: https://weights.replicate.delivery/default/InstantID/models--stablediffusionapi--nightvision-xl-0791.tar downloading to: checkpoints/models--stablediffusionapi--nightvision-xl-0791 2024-02-06T14:04:25Z | INFO | [ Initiating ] dest=checkpoints/models--stablediffusionapi--nightvision-xl-0791 minimum_chunk_size=150M url=https://weights.replicate.delivery/default/InstantID/models--stablediffusionapi--nightvision-xl-0791.tar 2024-02-06T14:04:33Z | INFO | [ Complete ] dest=checkpoints/models--stablediffusionapi--nightvision-xl-0791 size="6.9 GB" total_elapsed=8.690s url=https://weights.replicate.delivery/default/InstantID/models--stablediffusionapi--nightvision-xl-0791.tar downloading took: 9.307956218719482 [~] Loading new SDXL weights: checkpoints/models--stablediffusionapi--nightvision-xl-0791/ Keyword arguments {'safety_checker': None} are not expected by StableDiffusionXLInstantIDPipeline and will be ignored. Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s] Loading pipeline components...: 14%|█▍ | 1/7 [00:00<00:02, 2.25it/s] Loading pipeline components...: 43%|████▎ | 3/7 [00:00<00:00, 5.65it/s] Loading pipeline components...: 57%|█████▋ | 4/7 [00:00<00:00, 4.84it/s] Loading pipeline components...: 86%|████████▌ | 6/7 [00:02<00:00, 1.65it/s] Loading pipeline components...: 100%|██████████| 7/7 [00:02<00:00, 2.42it/s] [~] Seting up LCM (just in case) /root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/insightface/utils/transform.py:68: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions. To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`. P = np.linalg.lstsq(X_homo, Y)[0].T # Affine matrix. 3 x 4 Start inference... [Debug] Prompt: masterpiece painting, buildings in the backdrop, kaleidoscope, lilac orange blue cream fuchsia bright vivid gradient colors, the scene is cinematic, picture of woman, emotional realism, double exposure, watercolor ink pencil, graded wash, color layering, magic realism, figurative painting, intricate motifs, organic tracery, polished, [Debug] Neg Prompt: (lowres, low quality, worst quality:1.2), (text:1.2), watermark, (frame:1.2), deformed, ugly, deformed eyes, blur, out of focus, blurry, deformed cat, deformed, photo, anthropomorphic cat, monochrome, photo, pet collar, gun, weapon, blue, 3d, drones, drone, buildings in background, green 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:16, 1.79it/s] 7%|▋ | 2/30 [00:01<00:15, 1.79it/s] 10%|█ | 3/30 [00:01<00:15, 1.79it/s] 13%|█▎ | 4/30 [00:02<00:14, 1.78it/s] 17%|█▋ | 5/30 [00:02<00:14, 1.78it/s] 20%|██ | 6/30 [00:03<00:13, 1.78it/s] 23%|██▎ | 7/30 [00:03<00:12, 1.78it/s] 27%|██▋ | 8/30 [00:04<00:12, 1.78it/s] 30%|███ | 9/30 [00:05<00:11, 1.78it/s] 33%|███▎ | 10/30 [00:05<00:11, 1.77it/s] 37%|███▋ | 11/30 [00:06<00:10, 1.77it/s] 40%|████ | 12/30 [00:06<00:10, 1.77it/s] 43%|████▎ | 13/30 [00:07<00:09, 1.77it/s] 47%|████▋ | 14/30 [00:07<00:09, 1.77it/s] 50%|█████ | 15/30 [00:08<00:08, 1.77it/s] 53%|█████▎ | 16/30 [00:09<00:07, 1.77it/s] 57%|█████▋ | 17/30 [00:09<00:07, 1.77it/s] 60%|██████ | 18/30 [00:10<00:06, 1.77it/s] 63%|██████▎ | 19/30 [00:10<00:06, 1.77it/s] 67%|██████▋ | 20/30 [00:11<00:05, 1.77it/s] 70%|███████ | 21/30 [00:11<00:05, 1.77it/s] 73%|███████▎ | 22/30 [00:12<00:04, 1.77it/s] 77%|███████▋ | 23/30 [00:12<00:03, 1.77it/s] 80%|████████ | 24/30 [00:13<00:03, 1.77it/s] 83%|████████▎ | 25/30 [00:14<00:02, 1.77it/s] 87%|████████▋ | 26/30 [00:14<00:02, 1.77it/s] 90%|█████████ | 27/30 [00:15<00:01, 1.77it/s] 93%|█████████▎| 28/30 [00:15<00:01, 1.77it/s] 97%|█████████▋| 29/30 [00:16<00:00, 1.77it/s] 100%|██████████| 30/30 [00:16<00:00, 1.77it/s] 100%|██████████| 30/30 [00:16<00:00, 1.77it/s] NSFW content detected: False
Prediction
zsxkib/instant-id:2e4785a4IDnqgnbwp069rgg0cfs79rpergecStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedby @zsxkibInput
- prompt
- analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality
- scheduler
- EulerDiscreteScheduler
- enable_lcm
- num_outputs
- 1
- sdxl_weights
- protovision-xl-high-fidel
- output_format
- webp
- pose_strength
- 0.4
- canny_strength
- 0.3
- depth_strength
- 0.5
- guidance_scale
- 5
- output_quality
- 80
- negative_prompt
- (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured
- ip_adapter_scale
- 0.8
- lcm_guidance_scale
- 1.5
- num_inference_steps
- 30
- enable_pose_controlnet
- enhance_nonface_region
- enable_canny_controlnet
- enable_depth_controlnet
- lcm_num_inference_steps
- 5
- face_detection_input_width
- 640
- face_detection_input_height
- 640
- controlnet_conditioning_scale
- 0.8
{ "image": "https://replicate.delivery/pbxt/KIIutO7jIleskKaWebhvurgBUlHR6M6KN7KHaMMWSt4OnVrF/musk_resize.jpeg", "prompt": "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality", "scheduler": "EulerDiscreteScheduler", "enable_lcm": false, "pose_image": "https://replicate.delivery/pbxt/KJmFdQRQVDXGDVdVXftLvFrrvgOPXXRXbzIVEyExPYYOFPyF/80048a6e6586759dbcb529e74a9042ca.jpeg", "num_outputs": 1, "sdxl_weights": "protovision-xl-high-fidel", "output_format": "webp", "pose_strength": 0.4, "canny_strength": 0.3, "depth_strength": 0.5, "guidance_scale": 5, "output_quality": 80, "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured", "ip_adapter_scale": 0.8, "lcm_guidance_scale": 1.5, "num_inference_steps": 30, "enable_pose_controlnet": true, "enhance_nonface_region": true, "enable_canny_controlnet": false, "enable_depth_controlnet": false, "lcm_num_inference_steps": 5, "face_detection_input_width": 640, "face_detection_input_height": 640, "controlnet_conditioning_scale": 0.8 }
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 zsxkib/instant-id using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/instant-id:2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", { input: { image: "https://replicate.delivery/pbxt/KIIutO7jIleskKaWebhvurgBUlHR6M6KN7KHaMMWSt4OnVrF/musk_resize.jpeg", prompt: "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality", scheduler: "EulerDiscreteScheduler", enable_lcm: false, pose_image: "https://replicate.delivery/pbxt/KJmFdQRQVDXGDVdVXftLvFrrvgOPXXRXbzIVEyExPYYOFPyF/80048a6e6586759dbcb529e74a9042ca.jpeg", num_outputs: 1, sdxl_weights: "protovision-xl-high-fidel", output_format: "webp", pose_strength: 0.4, canny_strength: 0.3, depth_strength: 0.5, guidance_scale: 5, output_quality: 80, negative_prompt: "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured", ip_adapter_scale: 0.8, lcm_guidance_scale: 1.5, num_inference_steps: 30, enable_pose_controlnet: true, enhance_nonface_region: true, enable_canny_controlnet: false, enable_depth_controlnet: false, lcm_num_inference_steps: 5, face_detection_input_width: 640, face_detection_input_height: 640, controlnet_conditioning_scale: 0.8 } } ); 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 zsxkib/instant-id using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/instant-id:2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", input={ "image": "https://replicate.delivery/pbxt/KIIutO7jIleskKaWebhvurgBUlHR6M6KN7KHaMMWSt4OnVrF/musk_resize.jpeg", "prompt": "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality", "scheduler": "EulerDiscreteScheduler", "enable_lcm": False, "pose_image": "https://replicate.delivery/pbxt/KJmFdQRQVDXGDVdVXftLvFrrvgOPXXRXbzIVEyExPYYOFPyF/80048a6e6586759dbcb529e74a9042ca.jpeg", "num_outputs": 1, "sdxl_weights": "protovision-xl-high-fidel", "output_format": "webp", "pose_strength": 0.4, "canny_strength": 0.3, "depth_strength": 0.5, "guidance_scale": 5, "output_quality": 80, "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured", "ip_adapter_scale": 0.8, "lcm_guidance_scale": 1.5, "num_inference_steps": 30, "enable_pose_controlnet": True, "enhance_nonface_region": True, "enable_canny_controlnet": False, "enable_depth_controlnet": False, "lcm_num_inference_steps": 5, "face_detection_input_width": 640, "face_detection_input_height": 640, "controlnet_conditioning_scale": 0.8 } ) 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 zsxkib/instant-id 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": "2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", "input": { "image": "https://replicate.delivery/pbxt/KIIutO7jIleskKaWebhvurgBUlHR6M6KN7KHaMMWSt4OnVrF/musk_resize.jpeg", "prompt": "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality", "scheduler": "EulerDiscreteScheduler", "enable_lcm": false, "pose_image": "https://replicate.delivery/pbxt/KJmFdQRQVDXGDVdVXftLvFrrvgOPXXRXbzIVEyExPYYOFPyF/80048a6e6586759dbcb529e74a9042ca.jpeg", "num_outputs": 1, "sdxl_weights": "protovision-xl-high-fidel", "output_format": "webp", "pose_strength": 0.4, "canny_strength": 0.3, "depth_strength": 0.5, "guidance_scale": 5, "output_quality": 80, "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured", "ip_adapter_scale": 0.8, "lcm_guidance_scale": 1.5, "num_inference_steps": 30, "enable_pose_controlnet": true, "enhance_nonface_region": true, "enable_canny_controlnet": false, "enable_depth_controlnet": false, "lcm_num_inference_steps": 5, "face_detection_input_width": 640, "face_detection_input_height": 640, "controlnet_conditioning_scale": 0.8 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-05-30T14:08:04.881557Z", "created_at": "2024-05-30T14:07:28.818000Z", "data_removed": false, "error": null, "id": "nqgnbwp069rgg0cfs79rpergec", "input": { "image": "https://replicate.delivery/pbxt/KIIutO7jIleskKaWebhvurgBUlHR6M6KN7KHaMMWSt4OnVrF/musk_resize.jpeg", "prompt": "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality", "scheduler": "EulerDiscreteScheduler", "enable_lcm": false, "pose_image": "https://replicate.delivery/pbxt/KJmFdQRQVDXGDVdVXftLvFrrvgOPXXRXbzIVEyExPYYOFPyF/80048a6e6586759dbcb529e74a9042ca.jpeg", "num_outputs": 1, "sdxl_weights": "protovision-xl-high-fidel", "output_format": "webp", "pose_strength": 0.4, "canny_strength": 0.3, "depth_strength": 0.5, "guidance_scale": 5, "output_quality": 80, "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured", "ip_adapter_scale": 0.8, "lcm_guidance_scale": 1.5, "num_inference_steps": 30, "enable_pose_controlnet": true, "enhance_nonface_region": true, "enable_canny_controlnet": false, "enable_depth_controlnet": false, "lcm_num_inference_steps": 5, "face_detection_input_width": 640, "face_detection_input_height": 640, "controlnet_conditioning_scale": 0.8 }, "logs": "Using seed: 25815\n[~] Loading new SDXL weights: checkpoints/models--stablediffusionapi--protovision-xl-high-fidel/\nKeyword arguments {'safety_checker': None} are not expected by StableDiffusionXLInstantIDPipeline and will be ignored.\nLoading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]\nLoading pipeline components...: 29%|██▊ | 2/7 [00:00<00:00, 5.96it/s]\nLoading pipeline components...: 43%|████▎ | 3/7 [00:00<00:01, 3.94it/s]\nLoading pipeline components...: 71%|███████▏ | 5/7 [00:04<00:02, 1.15s/it]\nLoading pipeline components...: 100%|██████████| 7/7 [00:04<00:00, 1.48it/s]\nLoading pipeline components...: 100%|██████████| 7/7 [00:04<00:00, 1.50it/s]\n[~] Seting up LCM (just in case)\nStart inference...\n[Debug] Prompt: analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality,\n[Debug] Neg Prompt: (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:07, 4.12it/s]\n 7%|▋ | 2/30 [00:00<00:06, 4.12it/s]\n 10%|█ | 3/30 [00:00<00:06, 4.13it/s]\n 13%|█▎ | 4/30 [00:00<00:06, 4.12it/s]\n 17%|█▋ | 5/30 [00:01<00:06, 4.12it/s]\n 20%|██ | 6/30 [00:01<00:05, 4.12it/s]\n 23%|██▎ | 7/30 [00:01<00:05, 4.12it/s]\n 27%|██▋ | 8/30 [00:01<00:05, 4.12it/s]\n 30%|███ | 9/30 [00:02<00:05, 4.12it/s]\n 33%|███▎ | 10/30 [00:02<00:04, 4.12it/s]\n 37%|███▋ | 11/30 [00:02<00:04, 4.12it/s]\n 40%|████ | 12/30 [00:02<00:04, 4.12it/s]\n 43%|████▎ | 13/30 [00:03<00:04, 4.12it/s]\n 47%|████▋ | 14/30 [00:03<00:03, 4.12it/s]\n 50%|█████ | 15/30 [00:03<00:03, 4.12it/s]\n 53%|█████▎ | 16/30 [00:03<00:03, 4.12it/s]\n 57%|█████▋ | 17/30 [00:04<00:03, 4.12it/s]\n 60%|██████ | 18/30 [00:04<00:02, 4.12it/s]\n 63%|██████▎ | 19/30 [00:04<00:02, 4.11it/s]\n 67%|██████▋ | 20/30 [00:04<00:02, 4.11it/s]\n 70%|███████ | 21/30 [00:05<00:02, 4.10it/s]\n 73%|███████▎ | 22/30 [00:05<00:01, 4.10it/s]\n 77%|███████▋ | 23/30 [00:05<00:01, 4.10it/s]\n 80%|████████ | 24/30 [00:05<00:01, 4.09it/s]\n 83%|████████▎ | 25/30 [00:06<00:01, 4.10it/s]\n 87%|████████▋ | 26/30 [00:06<00:00, 4.10it/s]\n 90%|█████████ | 27/30 [00:06<00:00, 4.10it/s]\n 93%|█████████▎| 28/30 [00:06<00:00, 4.09it/s]\n 97%|█████████▋| 29/30 [00:07<00:00, 4.09it/s]\n100%|██████████| 30/30 [00:07<00:00, 4.09it/s]\n100%|██████████| 30/30 [00:07<00:00, 4.11it/s]\nNSFW content detected: False\n[~] Saving to /tmp/out_0.webp...\n[~] Output format: WEBP\n[~] Output quality: 80", "metrics": { "predict_time": 36.017849, "total_time": 36.063557 }, "output": [ "https://replicate.delivery/pbxt/J6l9A4W5SWK6NNTh9XXln5N6mk9Ge9FfMlC547bLezyISHzlA/out_0.webp" ], "started_at": "2024-05-30T14:07:28.863708Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/nqgnbwp069rgg0cfs79rpergec", "cancel": "https://api.replicate.com/v1/predictions/nqgnbwp069rgg0cfs79rpergec/cancel" }, "version": "f1ca369da43885a347690a98f6b710afbf5f167cb9bf13bd5af512ba4a9f7b63" }
Generated inUsing seed: 25815 [~] Loading new SDXL weights: checkpoints/models--stablediffusionapi--protovision-xl-high-fidel/ Keyword arguments {'safety_checker': None} are not expected by StableDiffusionXLInstantIDPipeline and will be ignored. Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s] Loading pipeline components...: 29%|██▊ | 2/7 [00:00<00:00, 5.96it/s] Loading pipeline components...: 43%|████▎ | 3/7 [00:00<00:01, 3.94it/s] Loading pipeline components...: 71%|███████▏ | 5/7 [00:04<00:02, 1.15s/it] Loading pipeline components...: 100%|██████████| 7/7 [00:04<00:00, 1.48it/s] Loading pipeline components...: 100%|██████████| 7/7 [00:04<00:00, 1.50it/s] [~] Seting up LCM (just in case) Start inference... [Debug] Prompt: analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality, [Debug] Neg Prompt: (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:07, 4.12it/s] 7%|▋ | 2/30 [00:00<00:06, 4.12it/s] 10%|█ | 3/30 [00:00<00:06, 4.13it/s] 13%|█▎ | 4/30 [00:00<00:06, 4.12it/s] 17%|█▋ | 5/30 [00:01<00:06, 4.12it/s] 20%|██ | 6/30 [00:01<00:05, 4.12it/s] 23%|██▎ | 7/30 [00:01<00:05, 4.12it/s] 27%|██▋ | 8/30 [00:01<00:05, 4.12it/s] 30%|███ | 9/30 [00:02<00:05, 4.12it/s] 33%|███▎ | 10/30 [00:02<00:04, 4.12it/s] 37%|███▋ | 11/30 [00:02<00:04, 4.12it/s] 40%|████ | 12/30 [00:02<00:04, 4.12it/s] 43%|████▎ | 13/30 [00:03<00:04, 4.12it/s] 47%|████▋ | 14/30 [00:03<00:03, 4.12it/s] 50%|█████ | 15/30 [00:03<00:03, 4.12it/s] 53%|█████▎ | 16/30 [00:03<00:03, 4.12it/s] 57%|█████▋ | 17/30 [00:04<00:03, 4.12it/s] 60%|██████ | 18/30 [00:04<00:02, 4.12it/s] 63%|██████▎ | 19/30 [00:04<00:02, 4.11it/s] 67%|██████▋ | 20/30 [00:04<00:02, 4.11it/s] 70%|███████ | 21/30 [00:05<00:02, 4.10it/s] 73%|███████▎ | 22/30 [00:05<00:01, 4.10it/s] 77%|███████▋ | 23/30 [00:05<00:01, 4.10it/s] 80%|████████ | 24/30 [00:05<00:01, 4.09it/s] 83%|████████▎ | 25/30 [00:06<00:01, 4.10it/s] 87%|████████▋ | 26/30 [00:06<00:00, 4.10it/s] 90%|█████████ | 27/30 [00:06<00:00, 4.10it/s] 93%|█████████▎| 28/30 [00:06<00:00, 4.09it/s] 97%|█████████▋| 29/30 [00:07<00:00, 4.09it/s] 100%|██████████| 30/30 [00:07<00:00, 4.09it/s] 100%|██████████| 30/30 [00:07<00:00, 4.11it/s] NSFW content detected: False [~] Saving to /tmp/out_0.webp... [~] Output format: WEBP [~] Output quality: 80
Prediction
zsxkib/instant-id:2e4785a4IDnqgnbwp069rgg0cfs79rpergecStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedby @zsxkibInput
- prompt
- analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality
- scheduler
- EulerDiscreteScheduler
- enable_lcm
- num_outputs
- 1
- sdxl_weights
- protovision-xl-high-fidel
- output_format
- webp
- pose_strength
- 0.4
- canny_strength
- 0.3
- depth_strength
- 0.5
- guidance_scale
- 5
- output_quality
- 80
- negative_prompt
- (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured
- ip_adapter_scale
- 0.8
- lcm_guidance_scale
- 1.5
- num_inference_steps
- 30
- enable_pose_controlnet
- enhance_nonface_region
- enable_canny_controlnet
- enable_depth_controlnet
- lcm_num_inference_steps
- 5
- face_detection_input_width
- 640
- face_detection_input_height
- 640
- controlnet_conditioning_scale
- 0.8
{ "image": "https://replicate.delivery/pbxt/KIIutO7jIleskKaWebhvurgBUlHR6M6KN7KHaMMWSt4OnVrF/musk_resize.jpeg", "prompt": "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality", "scheduler": "EulerDiscreteScheduler", "enable_lcm": false, "pose_image": "https://replicate.delivery/pbxt/KJmFdQRQVDXGDVdVXftLvFrrvgOPXXRXbzIVEyExPYYOFPyF/80048a6e6586759dbcb529e74a9042ca.jpeg", "num_outputs": 1, "sdxl_weights": "protovision-xl-high-fidel", "output_format": "webp", "pose_strength": 0.4, "canny_strength": 0.3, "depth_strength": 0.5, "guidance_scale": 5, "output_quality": 80, "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured", "ip_adapter_scale": 0.8, "lcm_guidance_scale": 1.5, "num_inference_steps": 30, "enable_pose_controlnet": true, "enhance_nonface_region": true, "enable_canny_controlnet": false, "enable_depth_controlnet": false, "lcm_num_inference_steps": 5, "face_detection_input_width": 640, "face_detection_input_height": 640, "controlnet_conditioning_scale": 0.8 }
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 zsxkib/instant-id using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/instant-id:2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", { input: { image: "https://replicate.delivery/pbxt/KIIutO7jIleskKaWebhvurgBUlHR6M6KN7KHaMMWSt4OnVrF/musk_resize.jpeg", prompt: "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality", scheduler: "EulerDiscreteScheduler", enable_lcm: false, pose_image: "https://replicate.delivery/pbxt/KJmFdQRQVDXGDVdVXftLvFrrvgOPXXRXbzIVEyExPYYOFPyF/80048a6e6586759dbcb529e74a9042ca.jpeg", num_outputs: 1, sdxl_weights: "protovision-xl-high-fidel", output_format: "webp", pose_strength: 0.4, canny_strength: 0.3, depth_strength: 0.5, guidance_scale: 5, output_quality: 80, negative_prompt: "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured", ip_adapter_scale: 0.8, lcm_guidance_scale: 1.5, num_inference_steps: 30, enable_pose_controlnet: true, enhance_nonface_region: true, enable_canny_controlnet: false, enable_depth_controlnet: false, lcm_num_inference_steps: 5, face_detection_input_width: 640, face_detection_input_height: 640, controlnet_conditioning_scale: 0.8 } } ); 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 zsxkib/instant-id using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/instant-id:2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", input={ "image": "https://replicate.delivery/pbxt/KIIutO7jIleskKaWebhvurgBUlHR6M6KN7KHaMMWSt4OnVrF/musk_resize.jpeg", "prompt": "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality", "scheduler": "EulerDiscreteScheduler", "enable_lcm": False, "pose_image": "https://replicate.delivery/pbxt/KJmFdQRQVDXGDVdVXftLvFrrvgOPXXRXbzIVEyExPYYOFPyF/80048a6e6586759dbcb529e74a9042ca.jpeg", "num_outputs": 1, "sdxl_weights": "protovision-xl-high-fidel", "output_format": "webp", "pose_strength": 0.4, "canny_strength": 0.3, "depth_strength": 0.5, "guidance_scale": 5, "output_quality": 80, "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured", "ip_adapter_scale": 0.8, "lcm_guidance_scale": 1.5, "num_inference_steps": 30, "enable_pose_controlnet": True, "enhance_nonface_region": True, "enable_canny_controlnet": False, "enable_depth_controlnet": False, "lcm_num_inference_steps": 5, "face_detection_input_width": 640, "face_detection_input_height": 640, "controlnet_conditioning_scale": 0.8 } ) 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 zsxkib/instant-id 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": "2e4785a4d80dadf580077b2244c8d7c05d8e3faac04a04c02d8e099dd2876789", "input": { "image": "https://replicate.delivery/pbxt/KIIutO7jIleskKaWebhvurgBUlHR6M6KN7KHaMMWSt4OnVrF/musk_resize.jpeg", "prompt": "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality", "scheduler": "EulerDiscreteScheduler", "enable_lcm": false, "pose_image": "https://replicate.delivery/pbxt/KJmFdQRQVDXGDVdVXftLvFrrvgOPXXRXbzIVEyExPYYOFPyF/80048a6e6586759dbcb529e74a9042ca.jpeg", "num_outputs": 1, "sdxl_weights": "protovision-xl-high-fidel", "output_format": "webp", "pose_strength": 0.4, "canny_strength": 0.3, "depth_strength": 0.5, "guidance_scale": 5, "output_quality": 80, "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured", "ip_adapter_scale": 0.8, "lcm_guidance_scale": 1.5, "num_inference_steps": 30, "enable_pose_controlnet": true, "enhance_nonface_region": true, "enable_canny_controlnet": false, "enable_depth_controlnet": false, "lcm_num_inference_steps": 5, "face_detection_input_width": 640, "face_detection_input_height": 640, "controlnet_conditioning_scale": 0.8 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-05-30T14:08:04.881557Z", "created_at": "2024-05-30T14:07:28.818000Z", "data_removed": false, "error": null, "id": "nqgnbwp069rgg0cfs79rpergec", "input": { "image": "https://replicate.delivery/pbxt/KIIutO7jIleskKaWebhvurgBUlHR6M6KN7KHaMMWSt4OnVrF/musk_resize.jpeg", "prompt": "analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality", "scheduler": "EulerDiscreteScheduler", "enable_lcm": false, "pose_image": "https://replicate.delivery/pbxt/KJmFdQRQVDXGDVdVXftLvFrrvgOPXXRXbzIVEyExPYYOFPyF/80048a6e6586759dbcb529e74a9042ca.jpeg", "num_outputs": 1, "sdxl_weights": "protovision-xl-high-fidel", "output_format": "webp", "pose_strength": 0.4, "canny_strength": 0.3, "depth_strength": 0.5, "guidance_scale": 5, "output_quality": 80, "negative_prompt": "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured", "ip_adapter_scale": 0.8, "lcm_guidance_scale": 1.5, "num_inference_steps": 30, "enable_pose_controlnet": true, "enhance_nonface_region": true, "enable_canny_controlnet": false, "enable_depth_controlnet": false, "lcm_num_inference_steps": 5, "face_detection_input_width": 640, "face_detection_input_height": 640, "controlnet_conditioning_scale": 0.8 }, "logs": "Using seed: 25815\n[~] Loading new SDXL weights: checkpoints/models--stablediffusionapi--protovision-xl-high-fidel/\nKeyword arguments {'safety_checker': None} are not expected by StableDiffusionXLInstantIDPipeline and will be ignored.\nLoading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]\nLoading pipeline components...: 29%|██▊ | 2/7 [00:00<00:00, 5.96it/s]\nLoading pipeline components...: 43%|████▎ | 3/7 [00:00<00:01, 3.94it/s]\nLoading pipeline components...: 71%|███████▏ | 5/7 [00:04<00:02, 1.15s/it]\nLoading pipeline components...: 100%|██████████| 7/7 [00:04<00:00, 1.48it/s]\nLoading pipeline components...: 100%|██████████| 7/7 [00:04<00:00, 1.50it/s]\n[~] Seting up LCM (just in case)\nStart inference...\n[Debug] Prompt: analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality,\n[Debug] Neg Prompt: (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:07, 4.12it/s]\n 7%|▋ | 2/30 [00:00<00:06, 4.12it/s]\n 10%|█ | 3/30 [00:00<00:06, 4.13it/s]\n 13%|█▎ | 4/30 [00:00<00:06, 4.12it/s]\n 17%|█▋ | 5/30 [00:01<00:06, 4.12it/s]\n 20%|██ | 6/30 [00:01<00:05, 4.12it/s]\n 23%|██▎ | 7/30 [00:01<00:05, 4.12it/s]\n 27%|██▋ | 8/30 [00:01<00:05, 4.12it/s]\n 30%|███ | 9/30 [00:02<00:05, 4.12it/s]\n 33%|███▎ | 10/30 [00:02<00:04, 4.12it/s]\n 37%|███▋ | 11/30 [00:02<00:04, 4.12it/s]\n 40%|████ | 12/30 [00:02<00:04, 4.12it/s]\n 43%|████▎ | 13/30 [00:03<00:04, 4.12it/s]\n 47%|████▋ | 14/30 [00:03<00:03, 4.12it/s]\n 50%|█████ | 15/30 [00:03<00:03, 4.12it/s]\n 53%|█████▎ | 16/30 [00:03<00:03, 4.12it/s]\n 57%|█████▋ | 17/30 [00:04<00:03, 4.12it/s]\n 60%|██████ | 18/30 [00:04<00:02, 4.12it/s]\n 63%|██████▎ | 19/30 [00:04<00:02, 4.11it/s]\n 67%|██████▋ | 20/30 [00:04<00:02, 4.11it/s]\n 70%|███████ | 21/30 [00:05<00:02, 4.10it/s]\n 73%|███████▎ | 22/30 [00:05<00:01, 4.10it/s]\n 77%|███████▋ | 23/30 [00:05<00:01, 4.10it/s]\n 80%|████████ | 24/30 [00:05<00:01, 4.09it/s]\n 83%|████████▎ | 25/30 [00:06<00:01, 4.10it/s]\n 87%|████████▋ | 26/30 [00:06<00:00, 4.10it/s]\n 90%|█████████ | 27/30 [00:06<00:00, 4.10it/s]\n 93%|█████████▎| 28/30 [00:06<00:00, 4.09it/s]\n 97%|█████████▋| 29/30 [00:07<00:00, 4.09it/s]\n100%|██████████| 30/30 [00:07<00:00, 4.09it/s]\n100%|██████████| 30/30 [00:07<00:00, 4.11it/s]\nNSFW content detected: False\n[~] Saving to /tmp/out_0.webp...\n[~] Output format: WEBP\n[~] Output quality: 80", "metrics": { "predict_time": 36.017849, "total_time": 36.063557 }, "output": [ "https://replicate.delivery/pbxt/J6l9A4W5SWK6NNTh9XXln5N6mk9Ge9FfMlC547bLezyISHzlA/out_0.webp" ], "started_at": "2024-05-30T14:07:28.863708Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/nqgnbwp069rgg0cfs79rpergec", "cancel": "https://api.replicate.com/v1/predictions/nqgnbwp069rgg0cfs79rpergec/cancel" }, "version": "f1ca369da43885a347690a98f6b710afbf5f167cb9bf13bd5af512ba4a9f7b63" }
Generated inUsing seed: 25815 [~] Loading new SDXL weights: checkpoints/models--stablediffusionapi--protovision-xl-high-fidel/ Keyword arguments {'safety_checker': None} are not expected by StableDiffusionXLInstantIDPipeline and will be ignored. Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s] Loading pipeline components...: 29%|██▊ | 2/7 [00:00<00:00, 5.96it/s] Loading pipeline components...: 43%|████▎ | 3/7 [00:00<00:01, 3.94it/s] Loading pipeline components...: 71%|███████▏ | 5/7 [00:04<00:02, 1.15s/it] Loading pipeline components...: 100%|██████████| 7/7 [00:04<00:00, 1.48it/s] Loading pipeline components...: 100%|██████████| 7/7 [00:04<00:00, 1.50it/s] [~] Seting up LCM (just in case) Start inference... [Debug] Prompt: analog film photo of a man. faded film, desaturated, 35mm photo, grainy, vignette, vintage, Kodachrome, Lomography, stained, highly detailed, found footage, masterpiece, best quality, [Debug] Neg Prompt: (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch, deformed, mutated, cross-eyed, ugly, disfigured (lowres, low quality, worst quality:1.2), (text:1.2), watermark, painting, drawing, illustration, glitch,deformed, mutated, cross-eyed, ugly, disfigured 0%| | 0/30 [00:00<?, ?it/s] 3%|▎ | 1/30 [00:00<00:07, 4.12it/s] 7%|▋ | 2/30 [00:00<00:06, 4.12it/s] 10%|█ | 3/30 [00:00<00:06, 4.13it/s] 13%|█▎ | 4/30 [00:00<00:06, 4.12it/s] 17%|█▋ | 5/30 [00:01<00:06, 4.12it/s] 20%|██ | 6/30 [00:01<00:05, 4.12it/s] 23%|██▎ | 7/30 [00:01<00:05, 4.12it/s] 27%|██▋ | 8/30 [00:01<00:05, 4.12it/s] 30%|███ | 9/30 [00:02<00:05, 4.12it/s] 33%|███▎ | 10/30 [00:02<00:04, 4.12it/s] 37%|███▋ | 11/30 [00:02<00:04, 4.12it/s] 40%|████ | 12/30 [00:02<00:04, 4.12it/s] 43%|████▎ | 13/30 [00:03<00:04, 4.12it/s] 47%|████▋ | 14/30 [00:03<00:03, 4.12it/s] 50%|█████ | 15/30 [00:03<00:03, 4.12it/s] 53%|█████▎ | 16/30 [00:03<00:03, 4.12it/s] 57%|█████▋ | 17/30 [00:04<00:03, 4.12it/s] 60%|██████ | 18/30 [00:04<00:02, 4.12it/s] 63%|██████▎ | 19/30 [00:04<00:02, 4.11it/s] 67%|██████▋ | 20/30 [00:04<00:02, 4.11it/s] 70%|███████ | 21/30 [00:05<00:02, 4.10it/s] 73%|███████▎ | 22/30 [00:05<00:01, 4.10it/s] 77%|███████▋ | 23/30 [00:05<00:01, 4.10it/s] 80%|████████ | 24/30 [00:05<00:01, 4.09it/s] 83%|████████▎ | 25/30 [00:06<00:01, 4.10it/s] 87%|████████▋ | 26/30 [00:06<00:00, 4.10it/s] 90%|█████████ | 27/30 [00:06<00:00, 4.10it/s] 93%|█████████▎| 28/30 [00:06<00:00, 4.09it/s] 97%|█████████▋| 29/30 [00:07<00:00, 4.09it/s] 100%|██████████| 30/30 [00:07<00:00, 4.09it/s] 100%|██████████| 30/30 [00:07<00:00, 4.11it/s] NSFW content detected: False [~] Saving to /tmp/out_0.webp... [~] Output format: WEBP [~] Output quality: 80
Want to make some of these yourself?
Run this model