Prediction
stability-ai/stable-diffusion:a9758cbfInput
- width
- 512
- height
- 512
- prompt
- Neil Armstrong on the Moon Canadian Flag
- num_outputs
- "4"
- guidance_scale
- "7"
- prompt_strength
- 0.8
- num_inference_steps
- "129"
{
"width": 512,
"height": 512,
"prompt": "Neil Armstrong on the Moon Canadian Flag",
"num_outputs": "4",
"guidance_scale": "7",
"prompt_strength": 0.8,
"num_inference_steps": "129"
}
npm install replicate
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run stability-ai/stable-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"stability-ai/stable-diffusion:a9758cbfbd5f3c2094457d996681af52552901775aa2d6dd0b17fd15df959bef",
{
input: {
width: 512,
height: 512,
prompt: "Neil Armstrong on the Moon Canadian Flag",
num_outputs: "4",
guidance_scale: "7",
prompt_strength: 0.8,
num_inference_steps: "129"
}
}
);
console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run stability-ai/stable-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"stability-ai/stable-diffusion:a9758cbfbd5f3c2094457d996681af52552901775aa2d6dd0b17fd15df959bef",
input={
"width": 512,
"height": 512,
"prompt": "Neil Armstrong on the Moon Canadian Flag",
"num_outputs": "4",
"guidance_scale": "7",
"prompt_strength": 0.8,
"num_inference_steps": "129"
}
)
print(output)
To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run stability-ai/stable-diffusion 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": "a9758cbfbd5f3c2094457d996681af52552901775aa2d6dd0b17fd15df959bef",
"input": {
"width": 512,
"height": 512,
"prompt": "Neil Armstrong on the Moon Canadian Flag",
"num_outputs": "4",
"guidance_scale": "7",
"prompt_strength": 0.8,
"num_inference_steps": "129"
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
brew install cog
If you don’t have Homebrew, there are other installation options available.
Pull and run stability-ai/stable-diffusion using Cog (this will download the full model and run it in your local environment):
cog predict r8.im/stability-ai/stable-diffusion@sha256:a9758cbfbd5f3c2094457d996681af52552901775aa2d6dd0b17fd15df959bef \
-i 'width=512' \
-i 'height=512' \
-i 'prompt="Neil Armstrong on the Moon Canadian Flag"' \
-i 'num_outputs="4"' \
-i 'guidance_scale="7"' \
-i 'prompt_strength=0.8' \
-i 'num_inference_steps="129"'
To learn more, take a look at the Cog documentation.
Pull and run stability-ai/stable-diffusion using Docker (this will download the full model and run it in your local environment):
docker run -d -p 5000:5000 --gpus=all r8.im/stability-ai/stable-diffusion@sha256:a9758cbfbd5f3c2094457d996681af52552901775aa2d6dd0b17fd15df959bef
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 512, "height": 512, "prompt": "Neil Armstrong on the Moon Canadian Flag", "num_outputs": "4", "guidance_scale": "7", "prompt_strength": 0.8, "num_inference_steps": "129" } }' \ http://localhost:5000/predictions
Output
{
"completed_at": "2022-09-06T00:42:47.498021Z",
"created_at": "2022-09-06T00:42:21.129738Z",
"data_removed": false,
"error": null,
"id": "xipb7ajpnretfmu42z3yxnhwuu",
"input": {
"width": 512,
"height": 512,
"prompt": "Neil Armstrong on the Moon Canadian Flag",
"num_outputs": "4",
"guidance_scale": "7",
"prompt_strength": 0.8,
"num_inference_steps": "129"
},
"logs": "Using seed: 47692\n\n0it [00:00, ?it/s]\n2it [00:00, 7.70it/s]\n3it [00:00, 6.60it/s]\n4it [00:00, 6.15it/s]\n5it [00:00, 5.93it/s]\n6it [00:00, 5.76it/s]\n7it [00:01, 5.69it/s]\n8it [00:01, 5.67it/s]\n9it [00:01, 5.64it/s]\n10it [00:01, 5.61it/s]\n11it [00:01, 5.59it/s]\n12it [00:02, 5.55it/s]\n13it [00:02, 5.58it/s]\n14it [00:02, 5.57it/s]\n15it [00:02, 5.57it/s]\n16it [00:02, 5.56it/s]\n17it [00:02, 5.56it/s]\n18it [00:03, 5.55it/s]\n19it [00:03, 5.48it/s]\n20it [00:03, 5.58it/s]\n21it [00:03, 5.57it/s]\n22it [00:03, 5.54it/s]\n23it [00:04, 5.55it/s]\n24it [00:04, 5.52it/s]\n25it [00:04, 5.56it/s]\n26it [00:04, 5.55it/s]\n27it [00:04, 5.55it/s]\n28it [00:04, 5.55it/s]\n29it [00:05, 5.56it/s]\n30it [00:05, 5.56it/s]\n31it [00:05, 5.51it/s]\n32it [00:05, 5.57it/s]\n33it [00:05, 5.57it/s]\n34it [00:06, 5.56it/s]\n35it [00:06, 5.56it/s]\n36it [00:06, 5.56it/s]\n37it [00:06, 5.55it/s]\n38it [00:06, 5.55it/s]\n39it [00:06, 5.55it/s]\n40it [00:07, 5.55it/s]\n41it [00:07, 5.55it/s]\n42it [00:07, 5.55it/s]\n43it [00:07, 5.55it/s]\n44it [00:07, 5.54it/s]\n45it [00:08, 5.55it/s]\n46it [00:08, 5.51it/s]\n47it [00:08, 5.56it/s]\n48it [00:08, 5.56it/s]\n49it [00:08, 5.55it/s]\n50it [00:08, 5.50it/s]\n51it [00:09, 5.55it/s]\n52it [00:09, 5.57it/s]\n53it [00:09, 5.56it/s]\n54it [00:09, 5.56it/s]\n55it [00:09, 5.55it/s]\n56it [00:09, 5.52it/s]\n57it [00:10, 5.56it/s]\n58it [00:10, 5.56it/s]\n59it [00:10, 5.56it/s]\n60it [00:10, 5.53it/s]\n61it [00:10, 5.51it/s]\n62it [00:11, 5.57it/s]\n63it [00:11, 5.56it/s]\n64it [00:11, 5.56it/s]\n65it [00:11, 5.56it/s]\n66it [00:11, 5.53it/s]\n67it [00:11, 5.55it/s]\n68it [00:12, 5.56it/s]\n69it [00:12, 5.56it/s]\n70it [00:12, 5.56it/s]\n71it [00:12, 5.55it/s]\n72it [00:12, 5.55it/s]\n73it [00:13, 5.55it/s]\n74it [00:13, 5.55it/s]\n75it [00:13, 5.53it/s]\n76it [00:13, 5.54it/s]\n77it [00:13, 5.55it/s]\n78it [00:13, 5.55it/s]\n79it [00:14, 5.55it/s]\n80it [00:14, 5.55it/s]\n81it [00:14, 5.54it/s]\n82it [00:14, 5.55it/s]\n83it [00:14, 5.55it/s]\n84it [00:15, 5.53it/s]\n85it [00:15, 5.56it/s]\n86it [00:15, 5.50it/s]\n87it [00:15, 5.57it/s]\n88it [00:15, 5.57it/s]\n89it [00:15, 5.56it/s]\n90it [00:16, 5.56it/s]\n91it [00:16, 5.53it/s]\n92it [00:16, 5.57it/s]\n93it [00:16, 5.56it/s]\n94it [00:16, 5.56it/s]\n95it [00:17, 5.56it/s]\n96it [00:17, 5.55it/s]\n97it [00:17, 5.55it/s]\n98it [00:17, 5.55it/s]\n99it [00:17, 5.55it/s]\n100it [00:17, 5.55it/s]\n101it [00:18, 5.53it/s]\n102it [00:18, 5.56it/s]\n103it [00:18, 5.56it/s]\n104it [00:18, 5.55it/s]\n105it [00:18, 5.56it/s]\n106it [00:19, 5.55it/s]\n107it [00:19, 5.55it/s]\n108it [00:19, 5.54it/s]\n109it [00:19, 5.55it/s]\n110it [00:19, 5.56it/s]\n111it [00:19, 5.54it/s]\n112it [00:20, 5.55it/s]\n113it [00:20, 5.55it/s]\n114it [00:20, 5.55it/s]\n115it [00:20, 5.55it/s]\n116it [00:20, 5.54it/s]\n117it [00:20, 5.55it/s]\n118it [00:21, 5.55it/s]\n119it [00:21, 5.55it/s]\n120it [00:21, 5.56it/s]\n121it [00:21, 5.55it/s]\n122it [00:21, 5.55it/s]\n123it [00:22, 5.55it/s]\n124it [00:22, 5.55it/s]\n125it [00:22, 5.55it/s]\n126it [00:22, 5.51it/s]\n127it [00:22, 5.56it/s]\n128it [00:22, 5.56it/s]\n129it [00:23, 5.56it/s]\n129it [00:23, 5.57it/s]",
"metrics": {
"predict_time": 26.133913,
"total_time": 26.368283
},
"output": [
"https://replicate.delivery/mgxm/1cc842cc-e11b-4cde-a648-85a0cb2a688e/out-0.png",
"https://replicate.delivery/mgxm/edfb8585-6e4c-40af-bad9-6b5e7756ae91/out-1.png",
"https://replicate.delivery/mgxm/68ca2fda-33e4-434a-8cfd-e662eb66b673/out-2.png",
"https://replicate.delivery/mgxm/c0d44518-0b94-4c9b-95e3-f0cee06edbc8/out-3.png"
],
"started_at": "2022-09-06T00:42:21.364108Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/xipb7ajpnretfmu42z3yxnhwuu",
"cancel": "https://api.replicate.com/v1/predictions/xipb7ajpnretfmu42z3yxnhwuu/cancel"
},
"version": "a9758cbfbd5f3c2094457d996681af52552901775aa2d6dd0b17fd15df959bef"
}
Using seed: 47692
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