zsxkib
/
sd3-controlnet
✨Stable Diffusion 3 w/ ⚡InstantX's Canny, Pose, and Tile ControlNets🖼️
Prediction
zsxkib/sd3-controlnet:1512680aIDr62c05e23xrgp0cg7b8ssxesmrStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- prompt
- vivid artistic style, women wearing a pinstripe suit
- structure
- tile
- input_image
- output_format
- webp
- control_weight
- 0.3
- guidance_scale
- 7
- output_quality
- 80
- inference_steps
- 25
- negative_prompt
- NSFW, nude, naked, porn, ugly
{ "prompt": "vivid artistic style, women wearing a pinstripe suit", "structure": "tile", "input_image": "https://replicate.delivery/pbxt/L8R5MODm9TDPWZnUMbAR06XQffs4NuBCJt0PML42PDd8s2vy/tile.jpg", "output_format": "webp", "control_weight": 0.3, "guidance_scale": 7, "output_quality": 80, "inference_steps": 25, "negative_prompt": "NSFW, nude, naked, porn, ugly" }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment 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/sd3-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/sd3-controlnet:1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6", { input: { prompt: "vivid artistic style, women wearing a pinstripe suit", structure: "tile", input_image: "https://replicate.delivery/pbxt/L8R5MODm9TDPWZnUMbAR06XQffs4NuBCJt0PML42PDd8s2vy/tile.jpg", output_format: "webp", control_weight: 0.3, guidance_scale: 7, output_quality: 80, inference_steps: 25, negative_prompt: "NSFW, nude, naked, porn, ugly" } } ); 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 replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun zsxkib/sd3-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/sd3-controlnet:1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6", input={ "prompt": "vivid artistic style, women wearing a pinstripe suit", "structure": "tile", "input_image": "https://replicate.delivery/pbxt/L8R5MODm9TDPWZnUMbAR06XQffs4NuBCJt0PML42PDd8s2vy/tile.jpg", "output_format": "webp", "control_weight": 0.3, "guidance_scale": 7, "output_quality": 80, "inference_steps": 25, "negative_prompt": "NSFW, nude, naked, porn, ugly" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run zsxkib/sd3-controlnet 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": "1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6", "input": { "prompt": "vivid artistic style, women wearing a pinstripe suit", "structure": "tile", "input_image": "https://replicate.delivery/pbxt/L8R5MODm9TDPWZnUMbAR06XQffs4NuBCJt0PML42PDd8s2vy/tile.jpg", "output_format": "webp", "control_weight": 0.3, "guidance_scale": 7, "output_quality": 80, "inference_steps": 25, "negative_prompt": "NSFW, nude, naked, porn, ugly" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/zsxkib/sd3-controlnet@sha256:1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6 \ -i 'prompt="vivid artistic style, women wearing a pinstripe suit"' \ -i 'structure="tile"' \ -i 'input_image="https://replicate.delivery/pbxt/L8R5MODm9TDPWZnUMbAR06XQffs4NuBCJt0PML42PDd8s2vy/tile.jpg"' \ -i 'output_format="webp"' \ -i 'control_weight=0.3' \ -i 'guidance_scale=7' \ -i 'output_quality=80' \ -i 'inference_steps=25' \ -i 'negative_prompt="NSFW, nude, naked, porn, ugly"'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/zsxkib/sd3-controlnet@sha256:1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "prompt": "vivid artistic style, women wearing a pinstripe suit", "structure": "tile", "input_image": "https://replicate.delivery/pbxt/L8R5MODm9TDPWZnUMbAR06XQffs4NuBCJt0PML42PDd8s2vy/tile.jpg", "output_format": "webp", "control_weight": 0.3, "guidance_scale": 7, "output_quality": 80, "inference_steps": 25, "negative_prompt": "NSFW, nude, naked, porn, ugly" } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-06-21T12:42:49.189217Z", "created_at": "2024-06-21T12:42:23.647000Z", "data_removed": false, "error": null, "id": "r62c05e23xrgp0cg7b8ssxesmr", "input": { "prompt": "vivid artistic style, women wearing a pinstripe suit", "structure": "tile", "input_image": "https://replicate.delivery/pbxt/L8R5MODm9TDPWZnUMbAR06XQffs4NuBCJt0PML42PDd8s2vy/tile.jpg", "output_format": "webp", "control_weight": 0.3, "guidance_scale": 7, "output_quality": 80, "inference_steps": 25, "negative_prompt": "NSFW, nude, naked, porn, ugly" }, "logs": "Using seed: 42020\nLoading pipeline components...: 0%| | 0/9 [00:00<?, ?it/s]\nLoading pipeline components...: 11%|█ | 1/9 [00:00<00:01, 4.30it/s]\nLoading pipeline components...: 44%|████▍ | 4/9 [00:03<00:05, 1.03s/it]\nLoading checkpoint shards: 0%| | 0/2 [00:00<?, ?it/s]\u001b[A\nLoading checkpoint shards: 50%|█████ | 1/2 [00:01<00:01, 1.27s/it]\u001b[A\nLoading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.05s/it]\u001b[A\nLoading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.08s/it]\nLoading pipeline components...: 56%|█████▌ | 5/9 [00:06<00:05, 1.36s/it]\nLoading pipeline components...: 78%|███████▊ | 7/9 [00:06<00:01, 1.25it/s]\nLoading pipeline components...: 100%|██████████| 9/9 [00:06<00:00, 1.67it/s]\nLoading pipeline components...: 100%|██████████| 9/9 [00:06<00:00, 1.32it/s]\n 0%| | 0/25 [00:00<?, ?it/s]\n 4%|▍ | 1/25 [00:00<00:07, 3.32it/s]\n 8%|▊ | 2/25 [00:00<00:06, 3.32it/s]\n 12%|█▏ | 3/25 [00:00<00:06, 3.30it/s]\n 16%|█▌ | 4/25 [00:01<00:06, 3.30it/s]\n 20%|██ | 5/25 [00:01<00:06, 3.31it/s]\n 24%|██▍ | 6/25 [00:01<00:05, 3.30it/s]\n 28%|██▊ | 7/25 [00:02<00:05, 3.30it/s]\n 32%|███▏ | 8/25 [00:02<00:05, 3.30it/s]\n 36%|███▌ | 9/25 [00:02<00:04, 3.30it/s]\n 40%|████ | 10/25 [00:03<00:04, 3.29it/s]\n 44%|████▍ | 11/25 [00:03<00:04, 3.30it/s]\n 48%|████▊ | 12/25 [00:03<00:03, 3.30it/s]\n 52%|█████▏ | 13/25 [00:03<00:03, 3.29it/s]\n 56%|█████▌ | 14/25 [00:04<00:03, 3.29it/s]\n 60%|██████ | 15/25 [00:04<00:03, 3.29it/s]\n 64%|██████▍ | 16/25 [00:04<00:02, 3.28it/s]\n 68%|██████▊ | 17/25 [00:05<00:02, 3.28it/s]\n 72%|███████▏ | 18/25 [00:05<00:02, 3.28it/s]\n 76%|███████▌ | 19/25 [00:05<00:01, 3.28it/s]\n 80%|████████ | 20/25 [00:06<00:01, 3.28it/s]\n 84%|████████▍ | 21/25 [00:06<00:01, 3.28it/s]\n 88%|████████▊ | 22/25 [00:06<00:00, 3.28it/s]\n 92%|█████████▏| 23/25 [00:06<00:00, 3.28it/s]\n 96%|█████████▌| 24/25 [00:07<00:00, 3.28it/s]\n100%|██████████| 25/25 [00:07<00:00, 3.28it/s]\n100%|██████████| 25/25 [00:07<00:00, 3.29it/s]\n[~] Saving to output.webp...\n[~] Output format: WEBP\n[~] Output quality: 80", "metrics": { "predict_time": 23.804016421, "total_time": 25.542217 }, "output": "https://replicate.delivery/pbxt/biya6fiLfDoMEE3ZMwOU3Kf38hnswmx29ZoDdBeHc0wg0JDMB/output.webp", "started_at": "2024-06-21T12:42:25.385200Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/r62c05e23xrgp0cg7b8ssxesmr", "cancel": "https://api.replicate.com/v1/predictions/r62c05e23xrgp0cg7b8ssxesmr/cancel" }, "version": "a8d23dad5ee7c2ac7269723fa8c1480da9b6edbfec17f6291f9d6c88835d9897" }Generated inUsing seed: 42020 Loading pipeline components...: 0%| | 0/9 [00:00<?, ?it/s] Loading pipeline components...: 11%|█ | 1/9 [00:00<00:01, 4.30it/s] Loading pipeline components...: 44%|████▍ | 4/9 [00:03<00:05, 1.03s/it] Loading checkpoint shards: 0%| | 0/2 [00:00<?, ?it/s] Loading checkpoint shards: 50%|█████ | 1/2 [00:01<00:01, 1.27s/it] Loading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.05s/it] Loading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.08s/it] Loading pipeline components...: 56%|█████▌ | 5/9 [00:06<00:05, 1.36s/it] Loading pipeline components...: 78%|███████▊ | 7/9 [00:06<00:01, 1.25it/s] Loading pipeline components...: 100%|██████████| 9/9 [00:06<00:00, 1.67it/s] Loading pipeline components...: 100%|██████████| 9/9 [00:06<00:00, 1.32it/s] 0%| | 0/25 [00:00<?, ?it/s] 4%|▍ | 1/25 [00:00<00:07, 3.32it/s] 8%|▊ | 2/25 [00:00<00:06, 3.32it/s] 12%|█▏ | 3/25 [00:00<00:06, 3.30it/s] 16%|█▌ | 4/25 [00:01<00:06, 3.30it/s] 20%|██ | 5/25 [00:01<00:06, 3.31it/s] 24%|██▍ | 6/25 [00:01<00:05, 3.30it/s] 28%|██▊ | 7/25 [00:02<00:05, 3.30it/s] 32%|███▏ | 8/25 [00:02<00:05, 3.30it/s] 36%|███▌ | 9/25 [00:02<00:04, 3.30it/s] 40%|████ | 10/25 [00:03<00:04, 3.29it/s] 44%|████▍ | 11/25 [00:03<00:04, 3.30it/s] 48%|████▊ | 12/25 [00:03<00:03, 3.30it/s] 52%|█████▏ | 13/25 [00:03<00:03, 3.29it/s] 56%|█████▌ | 14/25 [00:04<00:03, 3.29it/s] 60%|██████ | 15/25 [00:04<00:03, 3.29it/s] 64%|██████▍ | 16/25 [00:04<00:02, 3.28it/s] 68%|██████▊ | 17/25 [00:05<00:02, 3.28it/s] 72%|███████▏ | 18/25 [00:05<00:02, 3.28it/s] 76%|███████▌ | 19/25 [00:05<00:01, 3.28it/s] 80%|████████ | 20/25 [00:06<00:01, 3.28it/s] 84%|████████▍ | 21/25 [00:06<00:01, 3.28it/s] 88%|████████▊ | 22/25 [00:06<00:00, 3.28it/s] 92%|█████████▏| 23/25 [00:06<00:00, 3.28it/s] 96%|█████████▌| 24/25 [00:07<00:00, 3.28it/s] 100%|██████████| 25/25 [00:07<00:00, 3.28it/s] 100%|██████████| 25/25 [00:07<00:00, 3.29it/s] [~] Saving to output.webp... [~] Output format: WEBP [~] Output quality: 80Prediction
zsxkib/sd3-controlnet:1512680aIDzgrk8wzptnrgg0cg672s9x49drStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedby @zsxkibInput
- prompt
- A detailed image of a hand holding a smartphone. The smartphone is made entirely of vivid, colorful ecclesiastical stained glass, with intricate designs typical of church windows. The stained glass elements should be translucent, allowing light to pass through and creating a vibrant, luminous effect. The hand should be realistic and gently cradling the smartphone, emphasizing the contrast between modern technology and traditional stained glass artistry. Background should be neutral to highlight the details of the stained glass smartphone.
- input_image
- output_format
- webp
- control_weight
- 0.9
- guidance_scale
- 7
- output_quality
- 80
- inference_steps
- 25
- negative_prompt
- NSFW, nude, naked, porn, ugly
{ "prompt": "A detailed image of a hand holding a smartphone. The smartphone is made entirely of vivid, colorful ecclesiastical stained glass, with intricate designs typical of church windows. The stained glass elements should be translucent, allowing light to pass through and creating a vibrant, luminous effect. The hand should be realistic and gently cradling the smartphone, emphasizing the contrast between modern technology and traditional stained glass artistry. Background should be neutral to highlight the details of the stained glass smartphone.", "input_image": "https://replicate.delivery/pbxt/L7oQYWUw0SvS09BV8hSoV6wAB31oKPn4w9V0LP06Q2F98jnJ/Hand-Holding-Smartphone-Mockup-2-1536x1136.jpg", "output_format": "webp", "control_weight": 0.9, "guidance_scale": 7, "output_quality": 80, "inference_steps": 25, "negative_prompt": "NSFW, nude, naked, porn, ugly" }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment 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/sd3-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/sd3-controlnet:1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6", { input: { prompt: "A detailed image of a hand holding a smartphone. The smartphone is made entirely of vivid, colorful ecclesiastical stained glass, with intricate designs typical of church windows. The stained glass elements should be translucent, allowing light to pass through and creating a vibrant, luminous effect. The hand should be realistic and gently cradling the smartphone, emphasizing the contrast between modern technology and traditional stained glass artistry. Background should be neutral to highlight the details of the stained glass smartphone.", input_image: "https://replicate.delivery/pbxt/L7oQYWUw0SvS09BV8hSoV6wAB31oKPn4w9V0LP06Q2F98jnJ/Hand-Holding-Smartphone-Mockup-2-1536x1136.jpg", output_format: "webp", control_weight: 0.9, guidance_scale: 7, output_quality: 80, inference_steps: 25, negative_prompt: "NSFW, nude, naked, porn, ugly" } } ); 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 replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun zsxkib/sd3-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/sd3-controlnet:1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6", input={ "prompt": "A detailed image of a hand holding a smartphone. The smartphone is made entirely of vivid, colorful ecclesiastical stained glass, with intricate designs typical of church windows. The stained glass elements should be translucent, allowing light to pass through and creating a vibrant, luminous effect. The hand should be realistic and gently cradling the smartphone, emphasizing the contrast between modern technology and traditional stained glass artistry. Background should be neutral to highlight the details of the stained glass smartphone.", "input_image": "https://replicate.delivery/pbxt/L7oQYWUw0SvS09BV8hSoV6wAB31oKPn4w9V0LP06Q2F98jnJ/Hand-Holding-Smartphone-Mockup-2-1536x1136.jpg", "output_format": "webp", "control_weight": 0.9, "guidance_scale": 7, "output_quality": 80, "inference_steps": 25, "negative_prompt": "NSFW, nude, naked, porn, ugly" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run zsxkib/sd3-controlnet 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": "1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6", "input": { "prompt": "A detailed image of a hand holding a smartphone. The smartphone is made entirely of vivid, colorful ecclesiastical stained glass, with intricate designs typical of church windows. The stained glass elements should be translucent, allowing light to pass through and creating a vibrant, luminous effect. The hand should be realistic and gently cradling the smartphone, emphasizing the contrast between modern technology and traditional stained glass artistry. Background should be neutral to highlight the details of the stained glass smartphone.", "input_image": "https://replicate.delivery/pbxt/L7oQYWUw0SvS09BV8hSoV6wAB31oKPn4w9V0LP06Q2F98jnJ/Hand-Holding-Smartphone-Mockup-2-1536x1136.jpg", "output_format": "webp", "control_weight": 0.9, "guidance_scale": 7, "output_quality": 80, "inference_steps": 25, "negative_prompt": "NSFW, nude, naked, porn, ugly" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/zsxkib/sd3-controlnet@sha256:1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6 \ -i 'prompt="A detailed image of a hand holding a smartphone. The smartphone is made entirely of vivid, colorful ecclesiastical stained glass, with intricate designs typical of church windows. The stained glass elements should be translucent, allowing light to pass through and creating a vibrant, luminous effect. The hand should be realistic and gently cradling the smartphone, emphasizing the contrast between modern technology and traditional stained glass artistry. Background should be neutral to highlight the details of the stained glass smartphone."' \ -i 'input_image="https://replicate.delivery/pbxt/L7oQYWUw0SvS09BV8hSoV6wAB31oKPn4w9V0LP06Q2F98jnJ/Hand-Holding-Smartphone-Mockup-2-1536x1136.jpg"' \ -i 'output_format="webp"' \ -i 'control_weight=0.9' \ -i 'guidance_scale=7' \ -i 'output_quality=80' \ -i 'inference_steps=25' \ -i 'negative_prompt="NSFW, nude, naked, porn, ugly"'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/zsxkib/sd3-controlnet@sha256:1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "prompt": "A detailed image of a hand holding a smartphone. The smartphone is made entirely of vivid, colorful ecclesiastical stained glass, with intricate designs typical of church windows. The stained glass elements should be translucent, allowing light to pass through and creating a vibrant, luminous effect. The hand should be realistic and gently cradling the smartphone, emphasizing the contrast between modern technology and traditional stained glass artistry. Background should be neutral to highlight the details of the stained glass smartphone.", "input_image": "https://replicate.delivery/pbxt/L7oQYWUw0SvS09BV8hSoV6wAB31oKPn4w9V0LP06Q2F98jnJ/Hand-Holding-Smartphone-Mockup-2-1536x1136.jpg", "output_format": "webp", "control_weight": 0.9, "guidance_scale": 7, "output_quality": 80, "inference_steps": 25, "negative_prompt": "NSFW, nude, naked, porn, ugly" } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-06-19T18:33:05.896569Z", "created_at": "2024-06-19T18:32:55.765000Z", "data_removed": false, "error": null, "id": "zgrk8wzptnrgg0cg672s9x49dr", "input": { "prompt": "A detailed image of a hand holding a smartphone. The smartphone is made entirely of vivid, colorful ecclesiastical stained glass, with intricate designs typical of church windows. The stained glass elements should be translucent, allowing light to pass through and creating a vibrant, luminous effect. The hand should be realistic and gently cradling the smartphone, emphasizing the contrast between modern technology and traditional stained glass artistry. Background should be neutral to highlight the details of the stained glass smartphone.", "input_image": "https://replicate.delivery/pbxt/L7oQYWUw0SvS09BV8hSoV6wAB31oKPn4w9V0LP06Q2F98jnJ/Hand-Holding-Smartphone-Mockup-2-1536x1136.jpg", "output_format": "webp", "control_weight": 0.9, "guidance_scale": 7, "output_quality": 80, "inference_steps": 25, "negative_prompt": "NSFW, nude, naked, porn, ugly" }, "logs": "Using seed: 34433\nToken indices sequence length is longer than the specified maximum sequence length for this model (96 > 77). Running this sequence through the model will result in indexing errors\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['traditional stained glass artistry. background should be neutral to highlight the details of the stained glass smartphone.']\nToken indices sequence length is longer than the specified maximum sequence length for this model (96 > 77). Running this sequence through the model will result in indexing errors\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['traditional stained glass artistry. background should be neutral to highlight the details of the stained glass smartphone.']\n 0%| | 0/25 [00:00<?, ?it/s]\n 4%|▍ | 1/25 [00:00<00:07, 3.31it/s]\n 8%|▊ | 2/25 [00:00<00:06, 3.30it/s]\n 12%|█▏ | 3/25 [00:00<00:06, 3.26it/s]\n 16%|█▌ | 4/25 [00:01<00:06, 3.27it/s]\n 20%|██ | 5/25 [00:01<00:06, 3.27it/s]\n 24%|██▍ | 6/25 [00:01<00:05, 3.26it/s]\n 28%|██▊ | 7/25 [00:02<00:05, 3.26it/s]\n 32%|███▏ | 8/25 [00:02<00:05, 3.26it/s]\n 36%|███▌ | 9/25 [00:02<00:04, 3.26it/s]\n 40%|████ | 10/25 [00:03<00:04, 3.25it/s]\n 44%|████▍ | 11/25 [00:03<00:04, 3.26it/s]\n 48%|████▊ | 12/25 [00:03<00:03, 3.25it/s]\n 52%|█████▏ | 13/25 [00:03<00:03, 3.24it/s]\n 56%|█████▌ | 14/25 [00:04<00:03, 3.25it/s]\n 60%|██████ | 15/25 [00:04<00:03, 3.26it/s]\n 64%|██████▍ | 16/25 [00:04<00:02, 3.26it/s]\n 68%|██████▊ | 17/25 [00:05<00:02, 3.27it/s]\n 72%|███████▏ | 18/25 [00:05<00:02, 3.28it/s]\n 76%|███████▌ | 19/25 [00:05<00:01, 3.27it/s]\n 80%|████████ | 20/25 [00:06<00:01, 3.28it/s]\n 84%|████████▍ | 21/25 [00:06<00:01, 3.28it/s]\n 88%|████████▊ | 22/25 [00:06<00:00, 3.28it/s]\n 92%|█████████▏| 23/25 [00:07<00:00, 3.28it/s]\n 96%|█████████▌| 24/25 [00:07<00:00, 3.28it/s]\n100%|██████████| 25/25 [00:07<00:00, 3.28it/s]\n100%|██████████| 25/25 [00:07<00:00, 3.27it/s]\n[~] Saving to output.webp...\n[~] Output format: WEBP\n[~] Output quality: 80", "metrics": { "predict_time": 10.088725134, "total_time": 10.131569 }, "output": "https://replicate.delivery/pbxt/XJWcbqC9ylInEddwzVODUZJM8QRg0DdXWOjeWECw2o4wsGgJA/output.webp", "started_at": "2024-06-19T18:32:55.807844Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/zgrk8wzptnrgg0cg672s9x49dr", "cancel": "https://api.replicate.com/v1/predictions/zgrk8wzptnrgg0cg672s9x49dr/cancel" }, "version": "3fba667a81db1bdecbe641ed1a9d2ad04d532a3b543ce5d44acc96bf1fe7b733" }Generated inUsing seed: 34433 Token indices sequence length is longer than the specified maximum sequence length for this model (96 > 77). Running this sequence through the model will result in indexing errors The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['traditional stained glass artistry. background should be neutral to highlight the details of the stained glass smartphone.'] Token indices sequence length is longer than the specified maximum sequence length for this model (96 > 77). Running this sequence through the model will result in indexing errors The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['traditional stained glass artistry. background should be neutral to highlight the details of the stained glass smartphone.'] 0%| | 0/25 [00:00<?, ?it/s] 4%|▍ | 1/25 [00:00<00:07, 3.31it/s] 8%|▊ | 2/25 [00:00<00:06, 3.30it/s] 12%|█▏ | 3/25 [00:00<00:06, 3.26it/s] 16%|█▌ | 4/25 [00:01<00:06, 3.27it/s] 20%|██ | 5/25 [00:01<00:06, 3.27it/s] 24%|██▍ | 6/25 [00:01<00:05, 3.26it/s] 28%|██▊ | 7/25 [00:02<00:05, 3.26it/s] 32%|███▏ | 8/25 [00:02<00:05, 3.26it/s] 36%|███▌ | 9/25 [00:02<00:04, 3.26it/s] 40%|████ | 10/25 [00:03<00:04, 3.25it/s] 44%|████▍ | 11/25 [00:03<00:04, 3.26it/s] 48%|████▊ | 12/25 [00:03<00:03, 3.25it/s] 52%|█████▏ | 13/25 [00:03<00:03, 3.24it/s] 56%|█████▌ | 14/25 [00:04<00:03, 3.25it/s] 60%|██████ | 15/25 [00:04<00:03, 3.26it/s] 64%|██████▍ | 16/25 [00:04<00:02, 3.26it/s] 68%|██████▊ | 17/25 [00:05<00:02, 3.27it/s] 72%|███████▏ | 18/25 [00:05<00:02, 3.28it/s] 76%|███████▌ | 19/25 [00:05<00:01, 3.27it/s] 80%|████████ | 20/25 [00:06<00:01, 3.28it/s] 84%|████████▍ | 21/25 [00:06<00:01, 3.28it/s] 88%|████████▊ | 22/25 [00:06<00:00, 3.28it/s] 92%|█████████▏| 23/25 [00:07<00:00, 3.28it/s] 96%|█████████▌| 24/25 [00:07<00:00, 3.28it/s] 100%|██████████| 25/25 [00:07<00:00, 3.28it/s] 100%|██████████| 25/25 [00:07<00:00, 3.27it/s] [~] Saving to output.webp... [~] Output format: WEBP [~] Output quality: 80Prediction
zsxkib/sd3-controlnet:1512680aID4fk5h3cpbdrgj0cg7bdt5gxym4StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- prompt
- A stunning realistic dynamic shot of an astronaut with cowboy hat
- structure
- pose
- input_image
- output_format
- webp
- control_weight
- 0.5
- guidance_scale
- 6
- output_quality
- 80
- inference_steps
- 25
- negative_prompt
- NSFW, nude, naked, porn, ugly, helmet, astronaut helmet
{ "prompt": "A stunning realistic dynamic shot of an astronaut with cowboy hat", "structure": "pose", "input_image": "https://replicate.delivery/pbxt/L8R4ydzoL5fz4qIDSHi0R4PllEaGyV3pMjQyuNZQubhotI74/face-pose.jpg", "output_format": "webp", "control_weight": 0.5, "guidance_scale": 6, "output_quality": 80, "inference_steps": 25, "negative_prompt": "NSFW, nude, naked, porn, ugly, helmet, astronaut helmet" }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment 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/sd3-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/sd3-controlnet:1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6", { input: { prompt: "A stunning realistic dynamic shot of an astronaut with cowboy hat", structure: "pose", input_image: "https://replicate.delivery/pbxt/L8R4ydzoL5fz4qIDSHi0R4PllEaGyV3pMjQyuNZQubhotI74/face-pose.jpg", output_format: "webp", control_weight: 0.5, guidance_scale: 6, output_quality: 80, inference_steps: 25, negative_prompt: "NSFW, nude, naked, porn, ugly, helmet, astronaut helmet" } } ); 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 replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun zsxkib/sd3-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/sd3-controlnet:1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6", input={ "prompt": "A stunning realistic dynamic shot of an astronaut with cowboy hat", "structure": "pose", "input_image": "https://replicate.delivery/pbxt/L8R4ydzoL5fz4qIDSHi0R4PllEaGyV3pMjQyuNZQubhotI74/face-pose.jpg", "output_format": "webp", "control_weight": 0.5, "guidance_scale": 6, "output_quality": 80, "inference_steps": 25, "negative_prompt": "NSFW, nude, naked, porn, ugly, helmet, astronaut helmet" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run zsxkib/sd3-controlnet 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": "1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6", "input": { "prompt": "A stunning realistic dynamic shot of an astronaut with cowboy hat", "structure": "pose", "input_image": "https://replicate.delivery/pbxt/L8R4ydzoL5fz4qIDSHi0R4PllEaGyV3pMjQyuNZQubhotI74/face-pose.jpg", "output_format": "webp", "control_weight": 0.5, "guidance_scale": 6, "output_quality": 80, "inference_steps": 25, "negative_prompt": "NSFW, nude, naked, porn, ugly, helmet, astronaut helmet" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/zsxkib/sd3-controlnet@sha256:1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6 \ -i 'prompt="A stunning realistic dynamic shot of an astronaut with cowboy hat"' \ -i 'structure="pose"' \ -i 'input_image="https://replicate.delivery/pbxt/L8R4ydzoL5fz4qIDSHi0R4PllEaGyV3pMjQyuNZQubhotI74/face-pose.jpg"' \ -i 'output_format="webp"' \ -i 'control_weight=0.5' \ -i 'guidance_scale=6' \ -i 'output_quality=80' \ -i 'inference_steps=25' \ -i 'negative_prompt="NSFW, nude, naked, porn, ugly, helmet, astronaut helmet"'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/zsxkib/sd3-controlnet@sha256:1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "prompt": "A stunning realistic dynamic shot of an astronaut with cowboy hat", "structure": "pose", "input_image": "https://replicate.delivery/pbxt/L8R4ydzoL5fz4qIDSHi0R4PllEaGyV3pMjQyuNZQubhotI74/face-pose.jpg", "output_format": "webp", "control_weight": 0.5, "guidance_scale": 6, "output_quality": 80, "inference_steps": 25, "negative_prompt": "NSFW, nude, naked, porn, ugly, helmet, astronaut helmet" } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-06-21T12:53:28.510148Z", "created_at": "2024-06-21T12:53:07.803000Z", "data_removed": false, "error": null, "id": "4fk5h3cpbdrgj0cg7bdt5gxym4", "input": { "prompt": "A stunning realistic dynamic shot of an astronaut with cowboy hat", "structure": "pose", "input_image": "https://replicate.delivery/pbxt/L8R4ydzoL5fz4qIDSHi0R4PllEaGyV3pMjQyuNZQubhotI74/face-pose.jpg", "output_format": "webp", "control_weight": 0.5, "guidance_scale": 6, "output_quality": 80, "inference_steps": 25, "negative_prompt": "NSFW, nude, naked, porn, ugly, helmet, astronaut helmet" }, "logs": "Using seed: 16287\nLoading pipeline components...: 0%| | 0/9 [00:00<?, ?it/s]\nLoading pipeline components...: 11%|█ | 1/9 [00:00<00:01, 7.50it/s]\nLoading checkpoint shards: 0%| | 0/2 [00:00<?, ?it/s]\u001b[A\nLoading checkpoint shards: 50%|█████ | 1/2 [00:00<00:00, 1.05it/s]\u001b[A\nLoading checkpoint shards: 100%|██████████| 2/2 [00:01<00:00, 1.06it/s]\u001b[A\nLoading checkpoint shards: 100%|██████████| 2/2 [00:01<00:00, 1.06it/s]\nLoading pipeline components...: 33%|███▎ | 3/9 [00:02<00:04, 1.29it/s]\nLoading pipeline components...: 56%|█████▌ | 5/9 [00:02<00:02, 1.95it/s]\nLoading pipeline components...: 78%|███████▊ | 7/9 [00:04<00:01, 1.45it/s]\nLoading pipeline components...: 89%|████████▉ | 8/9 [00:04<00:00, 1.74it/s]\nLoading pipeline components...: 100%|██████████| 9/9 [00:04<00:00, 1.89it/s]\n 0%| | 0/25 [00:00<?, ?it/s]\n 4%|▍ | 1/25 [00:00<00:07, 3.27it/s]\n 8%|▊ | 2/25 [00:00<00:07, 3.26it/s]\n 12%|█▏ | 3/25 [00:00<00:06, 3.23it/s]\n 16%|█▌ | 4/25 [00:01<00:06, 3.24it/s]\n 20%|██ | 5/25 [00:01<00:06, 3.24it/s]\n 24%|██▍ | 6/25 [00:01<00:05, 3.23it/s]\n 28%|██▊ | 7/25 [00:02<00:05, 3.23it/s]\n 32%|███▏ | 8/25 [00:02<00:05, 3.24it/s]\n 36%|███▌ | 9/25 [00:02<00:04, 3.23it/s]\n 40%|████ | 10/25 [00:03<00:04, 3.24it/s]\n 44%|████▍ | 11/25 [00:03<00:04, 3.25it/s]\n 48%|████▊ | 12/25 [00:03<00:03, 3.26it/s]\n 52%|█████▏ | 13/25 [00:04<00:03, 3.25it/s]\n 56%|█████▌ | 14/25 [00:04<00:03, 3.26it/s]\n 60%|██████ | 15/25 [00:04<00:03, 3.26it/s]\n 64%|██████▍ | 16/25 [00:04<00:02, 3.26it/s]\n 68%|██████▊ | 17/25 [00:05<00:02, 3.26it/s]\n 72%|███████▏ | 18/25 [00:05<00:02, 3.26it/s]\n 76%|███████▌ | 19/25 [00:05<00:01, 3.26it/s]\n 80%|████████ | 20/25 [00:06<00:01, 3.26it/s]\n 84%|████████▍ | 21/25 [00:06<00:01, 3.26it/s]\n 88%|████████▊ | 22/25 [00:06<00:00, 3.26it/s]\n 92%|█████████▏| 23/25 [00:07<00:00, 3.25it/s]\n 96%|█████████▌| 24/25 [00:07<00:00, 3.26it/s]\n100%|██████████| 25/25 [00:07<00:00, 3.25it/s]\n100%|██████████| 25/25 [00:07<00:00, 3.25it/s]\n[~] Saving to output.webp...\n[~] Output format: WEBP\n[~] Output quality: 80", "metrics": { "predict_time": 20.667831938, "total_time": 20.707148 }, "output": "https://replicate.delivery/pbxt/ye4hfwfFtudVSIcGL2eB9nScPwe56FQTiAfeyPDv819jjTZgJA/output.webp", "started_at": "2024-06-21T12:53:07.842316Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/4fk5h3cpbdrgj0cg7bdt5gxym4", "cancel": "https://api.replicate.com/v1/predictions/4fk5h3cpbdrgj0cg7bdt5gxym4/cancel" }, "version": "a8d23dad5ee7c2ac7269723fa8c1480da9b6edbfec17f6291f9d6c88835d9897" }Generated inUsing seed: 16287 Loading pipeline components...: 0%| | 0/9 [00:00<?, ?it/s] Loading pipeline components...: 11%|█ | 1/9 [00:00<00:01, 7.50it/s] Loading checkpoint shards: 0%| | 0/2 [00:00<?, ?it/s] Loading checkpoint shards: 50%|█████ | 1/2 [00:00<00:00, 1.05it/s] Loading checkpoint shards: 100%|██████████| 2/2 [00:01<00:00, 1.06it/s] Loading checkpoint shards: 100%|██████████| 2/2 [00:01<00:00, 1.06it/s] Loading pipeline components...: 33%|███▎ | 3/9 [00:02<00:04, 1.29it/s] Loading pipeline components...: 56%|█████▌ | 5/9 [00:02<00:02, 1.95it/s] Loading pipeline components...: 78%|███████▊ | 7/9 [00:04<00:01, 1.45it/s] Loading pipeline components...: 89%|████████▉ | 8/9 [00:04<00:00, 1.74it/s] Loading pipeline components...: 100%|██████████| 9/9 [00:04<00:00, 1.89it/s] 0%| | 0/25 [00:00<?, ?it/s] 4%|▍ | 1/25 [00:00<00:07, 3.27it/s] 8%|▊ | 2/25 [00:00<00:07, 3.26it/s] 12%|█▏ | 3/25 [00:00<00:06, 3.23it/s] 16%|█▌ | 4/25 [00:01<00:06, 3.24it/s] 20%|██ | 5/25 [00:01<00:06, 3.24it/s] 24%|██▍ | 6/25 [00:01<00:05, 3.23it/s] 28%|██▊ | 7/25 [00:02<00:05, 3.23it/s] 32%|███▏ | 8/25 [00:02<00:05, 3.24it/s] 36%|███▌ | 9/25 [00:02<00:04, 3.23it/s] 40%|████ | 10/25 [00:03<00:04, 3.24it/s] 44%|████▍ | 11/25 [00:03<00:04, 3.25it/s] 48%|████▊ | 12/25 [00:03<00:03, 3.26it/s] 52%|█████▏ | 13/25 [00:04<00:03, 3.25it/s] 56%|█████▌ | 14/25 [00:04<00:03, 3.26it/s] 60%|██████ | 15/25 [00:04<00:03, 3.26it/s] 64%|██████▍ | 16/25 [00:04<00:02, 3.26it/s] 68%|██████▊ | 17/25 [00:05<00:02, 3.26it/s] 72%|███████▏ | 18/25 [00:05<00:02, 3.26it/s] 76%|███████▌ | 19/25 [00:05<00:01, 3.26it/s] 80%|████████ | 20/25 [00:06<00:01, 3.26it/s] 84%|████████▍ | 21/25 [00:06<00:01, 3.26it/s] 88%|████████▊ | 22/25 [00:06<00:00, 3.26it/s] 92%|█████████▏| 23/25 [00:07<00:00, 3.25it/s] 96%|█████████▌| 24/25 [00:07<00:00, 3.26it/s] 100%|██████████| 25/25 [00:07<00:00, 3.25it/s] 100%|██████████| 25/25 [00:07<00:00, 3.25it/s] [~] Saving to output.webp... [~] Output format: WEBP [~] Output quality: 80Prediction
zsxkib/sd3-controlnet:1512680aID9g6b0dqftdrgg0cg7h49p5tx44StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- prompt
- A surreal interpretation of an ice cream cone transforming into a fantastical cloud city, with miniature buildings and flying vehicles emerging from the swirls of ice cream
- structure
- canny
- input_image
- num_outputs
- 1
- aspect_ratio
- 1:1
- low_threshold
- 1
- output_format
- webp
- control_weight
- 0.7
- guidance_scale
- 7
- high_threshold
- 255
- output_quality
- 90
- inference_steps
- 20
- negative_prompt
- NSFW, nude, naked, porn, ugly, melting, dripping, realistic ice cream
{ "prompt": "A surreal interpretation of an ice cream cone transforming into a fantastical cloud city, with miniature buildings and flying vehicles emerging from the swirls of ice cream", "structure": "canny", "input_image": "https://replicate.delivery/pbxt/L8XLfd3JY13a51BlD1xA1APD4lPCqFgVJD5pG00Xpr4klsbQ/canny.png", "num_outputs": 1, "aspect_ratio": "1:1", "low_threshold": 1, "output_format": "webp", "control_weight": 0.7, "guidance_scale": 7, "high_threshold": 255, "output_quality": 90, "inference_steps": 20, "negative_prompt": "NSFW, nude, naked, porn, ugly, melting, dripping, realistic ice cream" }Install Replicate’s Node.js client library:npm install replicateSet theREPLICATE_API_TOKENenvironment 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/sd3-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/sd3-controlnet:1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6", { input: { prompt: "A surreal interpretation of an ice cream cone transforming into a fantastical cloud city, with miniature buildings and flying vehicles emerging from the swirls of ice cream", structure: "canny", input_image: "https://replicate.delivery/pbxt/L8XLfd3JY13a51BlD1xA1APD4lPCqFgVJD5pG00Xpr4klsbQ/canny.png", num_outputs: 1, aspect_ratio: "1:1", low_threshold: 1, output_format: "webp", control_weight: 0.7, guidance_scale: 7, high_threshold: 255, output_quality: 90, inference_steps: 20, negative_prompt: "NSFW, nude, naked, porn, ugly, melting, dripping, realistic ice cream" } } ); 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 replicateSet theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:import replicateRun zsxkib/sd3-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/sd3-controlnet:1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6", input={ "prompt": "A surreal interpretation of an ice cream cone transforming into a fantastical cloud city, with miniature buildings and flying vehicles emerging from the swirls of ice cream", "structure": "canny", "input_image": "https://replicate.delivery/pbxt/L8XLfd3JY13a51BlD1xA1APD4lPCqFgVJD5pG00Xpr4klsbQ/canny.png", "num_outputs": 1, "aspect_ratio": "1:1", "low_threshold": 1, "output_format": "webp", "control_weight": 0.7, "guidance_scale": 7, "high_threshold": 255, "output_quality": 90, "inference_steps": 20, "negative_prompt": "NSFW, nude, naked, porn, ugly, melting, dripping, realistic ice cream" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKENenvironment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run zsxkib/sd3-controlnet 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": "1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6", "input": { "prompt": "A surreal interpretation of an ice cream cone transforming into a fantastical cloud city, with miniature buildings and flying vehicles emerging from the swirls of ice cream", "structure": "canny", "input_image": "https://replicate.delivery/pbxt/L8XLfd3JY13a51BlD1xA1APD4lPCqFgVJD5pG00Xpr4klsbQ/canny.png", "num_outputs": 1, "aspect_ratio": "1:1", "low_threshold": 1, "output_format": "webp", "control_weight": 0.7, "guidance_scale": 7, "high_threshold": 255, "output_quality": 90, "inference_steps": 20, "negative_prompt": "NSFW, nude, naked, porn, ugly, melting, dripping, realistic ice cream" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/zsxkib/sd3-controlnet@sha256:1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6 \ -i 'prompt="A surreal interpretation of an ice cream cone transforming into a fantastical cloud city, with miniature buildings and flying vehicles emerging from the swirls of ice cream"' \ -i 'structure="canny"' \ -i 'input_image="https://replicate.delivery/pbxt/L8XLfd3JY13a51BlD1xA1APD4lPCqFgVJD5pG00Xpr4klsbQ/canny.png"' \ -i 'num_outputs=1' \ -i 'aspect_ratio="1:1"' \ -i 'low_threshold=1' \ -i 'output_format="webp"' \ -i 'control_weight=0.7' \ -i 'guidance_scale=7' \ -i 'high_threshold=255' \ -i 'output_quality=90' \ -i 'inference_steps=20' \ -i 'negative_prompt="NSFW, nude, naked, porn, ugly, melting, dripping, realistic ice cream"'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/zsxkib/sd3-controlnet@sha256:1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "prompt": "A surreal interpretation of an ice cream cone transforming into a fantastical cloud city, with miniature buildings and flying vehicles emerging from the swirls of ice cream", "structure": "canny", "input_image": "https://replicate.delivery/pbxt/L8XLfd3JY13a51BlD1xA1APD4lPCqFgVJD5pG00Xpr4klsbQ/canny.png", "num_outputs": 1, "aspect_ratio": "1:1", "low_threshold": 1, "output_format": "webp", "control_weight": 0.7, "guidance_scale": 7, "high_threshold": 255, "output_quality": 90, "inference_steps": 20, "negative_prompt": "NSFW, nude, naked, porn, ugly, melting, dripping, realistic ice cream" } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-06-21T19:32:19.903292Z", "created_at": "2024-06-21T19:32:11.347000Z", "data_removed": false, "error": null, "id": "9g6b0dqftdrgg0cg7h49p5tx44", "input": { "prompt": "A surreal interpretation of an ice cream cone transforming into a fantastical cloud city, with miniature buildings and flying vehicles emerging from the swirls of ice cream", "structure": "canny", "input_image": "https://replicate.delivery/pbxt/L8XLfd3JY13a51BlD1xA1APD4lPCqFgVJD5pG00Xpr4klsbQ/canny.png", "num_outputs": 1, "aspect_ratio": "1:1", "low_threshold": 1, "output_format": "webp", "control_weight": 0.7, "guidance_scale": 7, "high_threshold": 255, "output_quality": 90, "inference_steps": 20, "negative_prompt": "NSFW, nude, naked, porn, ugly, melting, dripping, realistic ice cream" }, "logs": "Using seed: 41082\nReusing existing pipeline for structure: canny\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:05, 3.32it/s]\n 10%|█ | 2/20 [00:00<00:05, 3.30it/s]\n 15%|█▌ | 3/20 [00:00<00:05, 3.28it/s]\n 20%|██ | 4/20 [00:01<00:04, 3.29it/s]\n 25%|██▌ | 5/20 [00:01<00:04, 3.29it/s]\n 30%|███ | 6/20 [00:01<00:04, 3.29it/s]\n 35%|███▌ | 7/20 [00:02<00:03, 3.28it/s]\n 40%|████ | 8/20 [00:02<00:03, 3.28it/s]\n 45%|████▌ | 9/20 [00:02<00:03, 3.28it/s]\n 50%|█████ | 10/20 [00:03<00:03, 3.28it/s]\n 55%|█████▌ | 11/20 [00:03<00:02, 3.29it/s]\n 60%|██████ | 12/20 [00:03<00:02, 3.30it/s]\n 65%|██████▌ | 13/20 [00:03<00:02, 3.30it/s]\n 70%|███████ | 14/20 [00:04<00:01, 3.30it/s]\n 75%|███████▌ | 15/20 [00:04<00:01, 3.30it/s]\n 80%|████████ | 16/20 [00:04<00:01, 3.31it/s]\n 85%|████████▌ | 17/20 [00:05<00:00, 3.31it/s]\n 90%|█████████ | 18/20 [00:05<00:00, 3.30it/s]\n 95%|█████████▌| 19/20 [00:05<00:00, 3.30it/s]\n100%|██████████| 20/20 [00:06<00:00, 3.30it/s]\n100%|██████████| 20/20 [00:06<00:00, 3.29it/s]\n[~] Saving to output_0.webp...\n[~] Output format: WEBP\n[~] Output quality: 90", "metrics": { "predict_time": 8.522457477, "total_time": 8.556292 }, "output": [ "https://replicate.delivery/pbxt/nba7X1PHtfXhTCoZ7ZbmnMkjFE4AUeVeQVVenAXZyXjL0hDMB/output_0.webp" ], "started_at": "2024-06-21T19:32:11.380834Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/9g6b0dqftdrgg0cg7h49p5tx44", "cancel": "https://api.replicate.com/v1/predictions/9g6b0dqftdrgg0cg7h49p5tx44/cancel" }, "version": "1512680a528ba127ad49e92e36780974e5aa12c7d717af83c4a98a9253adf2c6" }Generated inUsing seed: 41082 Reusing existing pipeline for structure: canny 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:05, 3.32it/s] 10%|█ | 2/20 [00:00<00:05, 3.30it/s] 15%|█▌ | 3/20 [00:00<00:05, 3.28it/s] 20%|██ | 4/20 [00:01<00:04, 3.29it/s] 25%|██▌ | 5/20 [00:01<00:04, 3.29it/s] 30%|███ | 6/20 [00:01<00:04, 3.29it/s] 35%|███▌ | 7/20 [00:02<00:03, 3.28it/s] 40%|████ | 8/20 [00:02<00:03, 3.28it/s] 45%|████▌ | 9/20 [00:02<00:03, 3.28it/s] 50%|█████ | 10/20 [00:03<00:03, 3.28it/s] 55%|█████▌ | 11/20 [00:03<00:02, 3.29it/s] 60%|██████ | 12/20 [00:03<00:02, 3.30it/s] 65%|██████▌ | 13/20 [00:03<00:02, 3.30it/s] 70%|███████ | 14/20 [00:04<00:01, 3.30it/s] 75%|███████▌ | 15/20 [00:04<00:01, 3.30it/s] 80%|████████ | 16/20 [00:04<00:01, 3.31it/s] 85%|████████▌ | 17/20 [00:05<00:00, 3.31it/s] 90%|█████████ | 18/20 [00:05<00:00, 3.30it/s] 95%|█████████▌| 19/20 [00:05<00:00, 3.30it/s] 100%|██████████| 20/20 [00:06<00:00, 3.30it/s] 100%|██████████| 20/20 [00:06<00:00, 3.29it/s] [~] Saving to output_0.webp... [~] Output format: WEBP [~] Output quality: 90
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