multitrickfox / waifu-diffusion-16bit
Waifu Diffusion v1.4 16bit
Prediction
multitrickfox/waifu-diffusion-16bit:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453IDfmcwcr5ufza3lag7qq3u3kj5umStatusSucceededSourceAPIHardwareT4Total durationCreatedInput
- width
- 512
- height
- 512
- num_outputs
- 1
- guidance_scale
- 6
- negative_prompt
- ugly
- positive_prompt
- charming, perfect kitsune girl
- num_inference_steps
- 50
{ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly", "positive_prompt": "charming, perfect kitsune girl", "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "multitrickfox/waifu-diffusion-16bit:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453", { input: { width: 512, height: 512, num_outputs: 1, guidance_scale: 6, negative_prompt: "ugly", positive_prompt: "charming, perfect kitsune girl", num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "multitrickfox/waifu-diffusion-16bit:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453", input={ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly", "positive_prompt": "charming, perfect kitsune girl", "num_inference_steps": 50 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run multitrickfox/waifu-diffusion-16bit 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": "multitrickfox/waifu-diffusion-16bit:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly", "positive_prompt": "charming, perfect kitsune girl", "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453 \ -i 'width=512' \ -i 'height=512' \ -i 'num_outputs=1' \ -i 'guidance_scale=6' \ -i 'negative_prompt="ugly"' \ -i 'positive_prompt="charming, perfect kitsune girl"' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly", "positive_prompt": "charming, perfect kitsune girl", "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2022-10-18T13:30:05.299076Z", "created_at": "2022-10-18T13:29:45.573599Z", "data_removed": false, "error": null, "id": "fmcwcr5ufza3lag7qq3u3kj5um", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly", "positive_prompt": "charming, perfect kitsune girl", "num_inference_steps": 50 }, "logs": "Using seed: 23536\nGlobal seed set to 23536\n\n0it [00:00, ?it/s]\n1it [00:03, 3.35s/it]\n2it [00:03, 1.50s/it]\n3it [00:03, 1.07it/s]\n4it [00:04, 1.50it/s]\n5it [00:04, 1.92it/s]\n6it [00:04, 2.31it/s]\n7it [00:04, 2.66it/s]\n8it [00:05, 2.95it/s]\n9it [00:05, 3.17it/s]\n10it [00:05, 3.35it/s]\n11it [00:05, 3.49it/s]\n12it [00:06, 3.59it/s]\n13it [00:06, 3.66it/s]\n14it [00:06, 3.70it/s]\n15it [00:06, 3.73it/s]\n16it [00:07, 3.76it/s]\n17it [00:07, 3.77it/s]\n18it [00:07, 3.78it/s]\n19it [00:07, 3.79it/s]\n20it [00:08, 3.78it/s]\n21it [00:08, 3.80it/s]\n22it [00:08, 3.79it/s]\n23it [00:09, 3.79it/s]\n24it [00:09, 3.80it/s]\n25it [00:09, 3.79it/s]\n26it [00:09, 3.79it/s]\n27it [00:10, 3.79it/s]\n28it [00:10, 3.79it/s]\n29it [00:10, 3.78it/s]\n30it [00:10, 3.78it/s]\n31it [00:11, 3.78it/s]\n32it [00:11, 3.79it/s]\n33it [00:11, 3.79it/s]\n34it [00:11, 3.80it/s]\n35it [00:12, 3.79it/s]\n36it [00:12, 3.79it/s]\n37it [00:12, 3.80it/s]\n38it [00:13, 3.80it/s]\n39it [00:13, 3.80it/s]\n40it [00:13, 3.80it/s]\n41it [00:13, 3.80it/s]\n42it [00:14, 3.80it/s]\n43it [00:14, 3.80it/s]\n44it [00:14, 3.81it/s]\n45it [00:14, 3.80it/s]\n46it [00:15, 3.81it/s]\n47it [00:15, 3.78it/s]\n48it [00:15, 3.79it/s]\n49it [00:15, 3.79it/s]\n50it [00:16, 3.79it/s]\n50it [00:16, 3.09it/s]", "metrics": { "predict_time": 19.813642, "total_time": 19.725477 }, "output": [ "https://replicate.delivery/pbxt/K5bcmkvJzCbJLtz4scQqWBXo35MHTdu1bYErRxcmD7ZXcx9D/out-0.png" ], "started_at": "2022-10-18T13:29:45.485434Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/fmcwcr5ufza3lag7qq3u3kj5um", "cancel": "https://api.replicate.com/v1/predictions/fmcwcr5ufza3lag7qq3u3kj5um/cancel" }, "version": "d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453" }
Generated inUsing seed: 23536 Global seed set to 23536 0it [00:00, ?it/s] 1it [00:03, 3.35s/it] 2it [00:03, 1.50s/it] 3it [00:03, 1.07it/s] 4it [00:04, 1.50it/s] 5it [00:04, 1.92it/s] 6it [00:04, 2.31it/s] 7it [00:04, 2.66it/s] 8it [00:05, 2.95it/s] 9it [00:05, 3.17it/s] 10it [00:05, 3.35it/s] 11it [00:05, 3.49it/s] 12it [00:06, 3.59it/s] 13it [00:06, 3.66it/s] 14it [00:06, 3.70it/s] 15it [00:06, 3.73it/s] 16it [00:07, 3.76it/s] 17it [00:07, 3.77it/s] 18it [00:07, 3.78it/s] 19it [00:07, 3.79it/s] 20it [00:08, 3.78it/s] 21it [00:08, 3.80it/s] 22it [00:08, 3.79it/s] 23it [00:09, 3.79it/s] 24it [00:09, 3.80it/s] 25it [00:09, 3.79it/s] 26it [00:09, 3.79it/s] 27it [00:10, 3.79it/s] 28it [00:10, 3.79it/s] 29it [00:10, 3.78it/s] 30it [00:10, 3.78it/s] 31it [00:11, 3.78it/s] 32it [00:11, 3.79it/s] 33it [00:11, 3.79it/s] 34it [00:11, 3.80it/s] 35it [00:12, 3.79it/s] 36it [00:12, 3.79it/s] 37it [00:12, 3.80it/s] 38it [00:13, 3.80it/s] 39it [00:13, 3.80it/s] 40it [00:13, 3.80it/s] 41it [00:13, 3.80it/s] 42it [00:14, 3.80it/s] 43it [00:14, 3.80it/s] 44it [00:14, 3.81it/s] 45it [00:14, 3.80it/s] 46it [00:15, 3.81it/s] 47it [00:15, 3.78it/s] 48it [00:15, 3.79it/s] 49it [00:15, 3.79it/s] 50it [00:16, 3.79it/s] 50it [00:16, 3.09it/s]
Prediction
multitrickfox/waifu-diffusion-16bit:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453ID5rfwgyrevnhgldk4fzto3ekcuyStatusSucceededSourceAPIHardwareT4Total durationCreatedInput
- width
- 512
- height
- 512
- num_outputs
- 1
- guidance_scale
- 6
- negative_prompt
- ugly, bad
- positive_prompt
- charming kitsune girl in kimono, cute fox tails and fox ears, perfect skin, beautiful face
- num_inference_steps
- 50
{ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, bad", "positive_prompt": "charming kitsune girl in kimono, cute fox tails and fox ears, perfect skin, beautiful face", "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "multitrickfox/waifu-diffusion-16bit:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453", { input: { width: 512, height: 512, num_outputs: 1, guidance_scale: 6, negative_prompt: "ugly, bad", positive_prompt: "charming kitsune girl in kimono, cute fox tails and fox ears, perfect skin, beautiful face", num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "multitrickfox/waifu-diffusion-16bit:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453", input={ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, bad", "positive_prompt": "charming kitsune girl in kimono, cute fox tails and fox ears, perfect skin, beautiful face", "num_inference_steps": 50 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run multitrickfox/waifu-diffusion-16bit 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": "multitrickfox/waifu-diffusion-16bit:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, bad", "positive_prompt": "charming kitsune girl in kimono, cute fox tails and fox ears, perfect skin, beautiful face", "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453 \ -i 'width=512' \ -i 'height=512' \ -i 'num_outputs=1' \ -i 'guidance_scale=6' \ -i 'negative_prompt="ugly, bad"' \ -i 'positive_prompt="charming kitsune girl in kimono, cute fox tails and fox ears, perfect skin, beautiful face"' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, bad", "positive_prompt": "charming kitsune girl in kimono, cute fox tails and fox ears, perfect skin, beautiful face", "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2022-10-18T16:44:18.619828Z", "created_at": "2022-10-18T16:44:03.769620Z", "data_removed": false, "error": null, "id": "5rfwgyrevnhgldk4fzto3ekcuy", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": 6, "negative_prompt": "ugly, bad", "positive_prompt": "charming kitsune girl in kimono, cute fox tails and fox ears, perfect skin, beautiful face", "num_inference_steps": 50 }, "logs": "Using seed: 55653\nGlobal seed set to 55653\n\n0it [00:00, ?it/s]\n1it [00:00, 6.91it/s]\n2it [00:00, 4.48it/s]\n3it [00:00, 4.04it/s]\n4it [00:00, 3.85it/s]\n5it [00:01, 3.70it/s]\n6it [00:01, 3.66it/s]\n7it [00:01, 3.64it/s]\n8it [00:02, 3.61it/s]\n9it [00:02, 3.59it/s]\n10it [00:02, 3.59it/s]\n11it [00:02, 3.58it/s]\n12it [00:03, 3.57it/s]\n13it [00:03, 3.56it/s]\n14it [00:03, 3.57it/s]\n15it [00:04, 3.57it/s]\n16it [00:04, 3.56it/s]\n17it [00:04, 3.55it/s]\n18it [00:04, 3.54it/s]\n19it [00:05, 3.54it/s]\n20it [00:05, 3.53it/s]\n21it [00:05, 3.54it/s]\n22it [00:06, 3.54it/s]\n23it [00:06, 3.53it/s]\n24it [00:06, 3.53it/s]\n25it [00:06, 3.53it/s]\n26it [00:07, 3.53it/s]\n27it [00:07, 3.53it/s]\n28it [00:07, 3.53it/s]\n29it [00:08, 3.52it/s]\n30it [00:08, 3.51it/s]\n31it [00:08, 3.51it/s]\n32it [00:08, 3.52it/s]\n33it [00:09, 3.51it/s]\n34it [00:09, 3.51it/s]\n35it [00:09, 3.50it/s]\n36it [00:10, 3.51it/s]\n37it [00:10, 3.51it/s]\n38it [00:10, 3.50it/s]\n39it [00:10, 3.49it/s]\n40it [00:11, 3.49it/s]\n41it [00:11, 3.49it/s]\n42it [00:11, 3.49it/s]\n43it [00:12, 3.50it/s]\n44it [00:12, 3.49it/s]\n45it [00:12, 3.48it/s]\n46it [00:12, 3.48it/s]\n47it [00:13, 3.49it/s]\n48it [00:13, 3.48it/s]\n49it [00:13, 3.48it/s]\n50it [00:14, 3.48it/s]\n50it [00:14, 3.56it/s]", "metrics": { "predict_time": 14.875456, "total_time": 14.850208 }, "output": [ "https://replicate.delivery/pbxt/DFZ4coihoPbGEdXy73VjQ4qCvwb304wWjCflFUyWBJbxTk7HA/out-0.png" ], "started_at": "2022-10-18T16:44:03.744372Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/5rfwgyrevnhgldk4fzto3ekcuy", "cancel": "https://api.replicate.com/v1/predictions/5rfwgyrevnhgldk4fzto3ekcuy/cancel" }, "version": "d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453" }
Generated inUsing seed: 55653 Global seed set to 55653 0it [00:00, ?it/s] 1it [00:00, 6.91it/s] 2it [00:00, 4.48it/s] 3it [00:00, 4.04it/s] 4it [00:00, 3.85it/s] 5it [00:01, 3.70it/s] 6it [00:01, 3.66it/s] 7it [00:01, 3.64it/s] 8it [00:02, 3.61it/s] 9it [00:02, 3.59it/s] 10it [00:02, 3.59it/s] 11it [00:02, 3.58it/s] 12it [00:03, 3.57it/s] 13it [00:03, 3.56it/s] 14it [00:03, 3.57it/s] 15it [00:04, 3.57it/s] 16it [00:04, 3.56it/s] 17it [00:04, 3.55it/s] 18it [00:04, 3.54it/s] 19it [00:05, 3.54it/s] 20it [00:05, 3.53it/s] 21it [00:05, 3.54it/s] 22it [00:06, 3.54it/s] 23it [00:06, 3.53it/s] 24it [00:06, 3.53it/s] 25it [00:06, 3.53it/s] 26it [00:07, 3.53it/s] 27it [00:07, 3.53it/s] 28it [00:07, 3.53it/s] 29it [00:08, 3.52it/s] 30it [00:08, 3.51it/s] 31it [00:08, 3.51it/s] 32it [00:08, 3.52it/s] 33it [00:09, 3.51it/s] 34it [00:09, 3.51it/s] 35it [00:09, 3.50it/s] 36it [00:10, 3.51it/s] 37it [00:10, 3.51it/s] 38it [00:10, 3.50it/s] 39it [00:10, 3.49it/s] 40it [00:11, 3.49it/s] 41it [00:11, 3.49it/s] 42it [00:11, 3.49it/s] 43it [00:12, 3.50it/s] 44it [00:12, 3.49it/s] 45it [00:12, 3.48it/s] 46it [00:12, 3.48it/s] 47it [00:13, 3.49it/s] 48it [00:13, 3.48it/s] 49it [00:13, 3.48it/s] 50it [00:14, 3.48it/s] 50it [00:14, 3.56it/s]
Prediction
multitrickfox/waifu-diffusion-16bit:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453IDw7rfu44vwva5nllwzdxyzj7ysiStatusSucceededSourceAPIHardwareT4Total durationCreatedInput
- width
- 512
- height
- 512
- num_outputs
- 1
- guidance_scale
- 6
- positive_prompt
- charming kitsune girl
- num_inference_steps
- 50
{ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": 6, "positive_prompt": "charming kitsune girl", "num_inference_steps": 50 }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "multitrickfox/waifu-diffusion-16bit:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453", { input: { width: 512, height: 512, num_outputs: 1, guidance_scale: 6, positive_prompt: "charming kitsune girl", num_inference_steps: 50 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "multitrickfox/waifu-diffusion-16bit:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453", input={ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": 6, "positive_prompt": "charming kitsune girl", "num_inference_steps": 50 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run multitrickfox/waifu-diffusion-16bit 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": "multitrickfox/waifu-diffusion-16bit:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": 6, "positive_prompt": "charming kitsune girl", "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453 \ -i 'width=512' \ -i 'height=512' \ -i 'num_outputs=1' \ -i 'guidance_scale=6' \ -i 'positive_prompt="charming kitsune girl"' \ -i 'num_inference_steps=50'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": 6, "positive_prompt": "charming kitsune girl", "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2022-10-18T13:31:33.242623Z", "created_at": "2022-10-18T13:31:18.842949Z", "data_removed": false, "error": null, "id": "w7rfu44vwva5nllwzdxyzj7ysi", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": 6, "positive_prompt": "charming kitsune girl", "num_inference_steps": 50 }, "logs": "Using seed: 35820\nGlobal seed set to 35820\n\n0it [00:00, ?it/s]\n1it [00:00, 6.88it/s]\n2it [00:00, 4.25it/s]\n3it [00:00, 4.01it/s]\n4it [00:00, 3.90it/s]\n5it [00:01, 3.81it/s]\n6it [00:01, 3.75it/s]\n7it [00:01, 3.75it/s]\n8it [00:02, 3.74it/s]\n9it [00:02, 3.71it/s]\n10it [00:02, 3.69it/s]\n11it [00:02, 3.70it/s]\n12it [00:03, 3.70it/s]\n13it [00:03, 3.66it/s]\n14it [00:03, 3.67it/s]\n15it [00:03, 3.68it/s]\n16it [00:04, 3.67it/s]\n17it [00:04, 3.66it/s]\n18it [00:04, 3.66it/s]\n19it [00:05, 3.67it/s]\n20it [00:05, 3.67it/s]\n21it [00:05, 3.65it/s]\n22it [00:05, 3.65it/s]\n23it [00:06, 3.65it/s]\n24it [00:06, 3.65it/s]\n25it [00:06, 3.65it/s]\n26it [00:06, 3.67it/s]\n27it [00:07, 3.65it/s]\n28it [00:07, 3.65it/s]\n29it [00:07, 3.65it/s]\n30it [00:08, 3.65it/s]\n31it [00:08, 3.64it/s]\n32it [00:08, 3.62it/s]\n33it [00:08, 3.63it/s]\n34it [00:09, 3.64it/s]\n35it [00:09, 3.63it/s]\n36it [00:09, 3.63it/s]\n37it [00:10, 3.62it/s]\n38it [00:10, 3.61it/s]\n39it [00:10, 3.61it/s]\n40it [00:10, 3.61it/s]\n41it [00:11, 3.62it/s]\n42it [00:11, 3.61it/s]\n43it [00:11, 3.61it/s]\n44it [00:11, 3.60it/s]\n45it [00:12, 3.60it/s]\n46it [00:12, 3.60it/s]\n47it [00:12, 3.61it/s]\n48it [00:13, 3.61it/s]\n49it [00:13, 3.61it/s]\n50it [00:13, 3.61it/s]\n50it [00:13, 3.67it/s]", "metrics": { "predict_time": 14.425856, "total_time": 14.399674 }, "output": [ "https://replicate.delivery/pbxt/9KjfUvlEScT8Ny2RRagP9ZGwbyigpuZgx7lkKi5Pjmga5i7HA/out-0.png" ], "started_at": "2022-10-18T13:31:18.816767Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/w7rfu44vwva5nllwzdxyzj7ysi", "cancel": "https://api.replicate.com/v1/predictions/w7rfu44vwva5nllwzdxyzj7ysi/cancel" }, "version": "d79228478508623d9192cfbf39c9fe089d9db7e1dc51cd1c4d266cd58b138453" }
Generated inUsing seed: 35820 Global seed set to 35820 0it [00:00, ?it/s] 1it [00:00, 6.88it/s] 2it [00:00, 4.25it/s] 3it [00:00, 4.01it/s] 4it [00:00, 3.90it/s] 5it [00:01, 3.81it/s] 6it [00:01, 3.75it/s] 7it [00:01, 3.75it/s] 8it [00:02, 3.74it/s] 9it [00:02, 3.71it/s] 10it [00:02, 3.69it/s] 11it [00:02, 3.70it/s] 12it [00:03, 3.70it/s] 13it [00:03, 3.66it/s] 14it [00:03, 3.67it/s] 15it [00:03, 3.68it/s] 16it [00:04, 3.67it/s] 17it [00:04, 3.66it/s] 18it [00:04, 3.66it/s] 19it [00:05, 3.67it/s] 20it [00:05, 3.67it/s] 21it [00:05, 3.65it/s] 22it [00:05, 3.65it/s] 23it [00:06, 3.65it/s] 24it [00:06, 3.65it/s] 25it [00:06, 3.65it/s] 26it [00:06, 3.67it/s] 27it [00:07, 3.65it/s] 28it [00:07, 3.65it/s] 29it [00:07, 3.65it/s] 30it [00:08, 3.65it/s] 31it [00:08, 3.64it/s] 32it [00:08, 3.62it/s] 33it [00:08, 3.63it/s] 34it [00:09, 3.64it/s] 35it [00:09, 3.63it/s] 36it [00:09, 3.63it/s] 37it [00:10, 3.62it/s] 38it [00:10, 3.61it/s] 39it [00:10, 3.61it/s] 40it [00:10, 3.61it/s] 41it [00:11, 3.62it/s] 42it [00:11, 3.61it/s] 43it [00:11, 3.61it/s] 44it [00:11, 3.60it/s] 45it [00:12, 3.60it/s] 46it [00:12, 3.60it/s] 47it [00:12, 3.61it/s] 48it [00:13, 3.61it/s] 49it [00:13, 3.61it/s] 50it [00:13, 3.61it/s] 50it [00:13, 3.67it/s]
Prediction
multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2bIDhgeif32fvncqvnhoomsbfczqruStatusSucceededSourceWebHardwareT4Total durationCreatedInput
- width
- 512
- height
- 512
- num_outputs
- 1
- guidance_scale
- "6"
- negative_prompt
- 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, artist name
- positive_prompt
- masterpiece, best quality, charming, perfect kitsune girl
- num_inference_steps
- "50"
{ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", { input: { width: 512, height: 512, num_outputs: 1, guidance_scale: "6", negative_prompt: "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, artist name", positive_prompt: "masterpiece, best quality, charming, perfect kitsune girl", num_inference_steps: "50" } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", input={ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run multitrickfox/waifu-diffusion-16bit 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": "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b \ -i 'width=512' \ -i 'height=512' \ -i 'num_outputs=1' \ -i 'guidance_scale="6"' \ -i 'negative_prompt="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, artist name"' \ -i 'positive_prompt="masterpiece, best quality, charming, perfect kitsune girl"' \ -i 'num_inference_steps="50"'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2022-11-03T22:31:51.476442Z", "created_at": "2022-11-03T22:31:37.750302Z", "data_removed": false, "error": null, "id": "hgeif32fvncqvnhoomsbfczqru", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" }, "logs": "Using seed: 1497\n\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:16, 2.90it/s]\n 4%|▍ | 2/50 [00:00<00:14, 3.43it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.64it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.73it/s]\n 10%|█ | 5/50 [00:01<00:11, 3.75it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.79it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.81it/s]\n 16%|█▌ | 8/50 [00:02<00:10, 3.83it/s]\n 18%|█▊ | 9/50 [00:02<00:10, 3.82it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.83it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.84it/s]\n 24%|██▍ | 12/50 [00:03<00:09, 3.85it/s]\n 26%|██▌ | 13/50 [00:03<00:09, 3.85it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.85it/s]\n 30%|███ | 15/50 [00:03<00:09, 3.85it/s]\n 32%|███▏ | 16/50 [00:04<00:08, 3.85it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.85it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.84it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.85it/s]\n 40%|████ | 20/50 [00:05<00:07, 3.85it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.84it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.84it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.84it/s]\n 48%|████▊ | 24/50 [00:06<00:06, 3.85it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.85it/s]\n 52%|█████▏ | 26/50 [00:06<00:06, 3.85it/s]\n 54%|█████▍ | 27/50 [00:07<00:05, 3.85it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.85it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.85it/s]\n 60%|██████ | 30/50 [00:07<00:05, 3.85it/s]\n 62%|██████▏ | 31/50 [00:08<00:04, 3.85it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.84it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.83it/s]\n 68%|██████▊ | 34/50 [00:08<00:04, 3.84it/s]\n 70%|███████ | 35/50 [00:09<00:03, 3.84it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.84it/s]\n 74%|███████▍ | 37/50 [00:09<00:03, 3.85it/s]\n 76%|███████▌ | 38/50 [00:09<00:03, 3.84it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.83it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.84it/s]\n 82%|████████▏ | 41/50 [00:10<00:02, 3.84it/s]\n 84%|████████▍ | 42/50 [00:10<00:02, 3.84it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.84it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.84it/s]\n 90%|█████████ | 45/50 [00:11<00:01, 3.82it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.83it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.83it/s]\n 96%|█████████▌| 48/50 [00:12<00:00, 3.84it/s]\n 98%|█████████▊| 49/50 [00:12<00:00, 3.83it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.84it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.82it/s]", "metrics": { "predict_time": 13.686963, "total_time": 13.72614 }, "output": [ "https://replicate.delivery/pbxt/ZoXfbWC0UST0di7RMbaG9kuIwGYrh5kGLxTzukyEPHprmPePA/out-0.png" ], "started_at": "2022-11-03T22:31:37.789479Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/hgeif32fvncqvnhoomsbfczqru", "cancel": "https://api.replicate.com/v1/predictions/hgeif32fvncqvnhoomsbfczqru/cancel" }, "version": "d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b" }
Generated inUsing seed: 1497 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:16, 2.90it/s] 4%|▍ | 2/50 [00:00<00:14, 3.43it/s] 6%|▌ | 3/50 [00:00<00:12, 3.64it/s] 8%|▊ | 4/50 [00:01<00:12, 3.73it/s] 10%|█ | 5/50 [00:01<00:11, 3.75it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.79it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.81it/s] 16%|█▌ | 8/50 [00:02<00:10, 3.83it/s] 18%|█▊ | 9/50 [00:02<00:10, 3.82it/s] 20%|██ | 10/50 [00:02<00:10, 3.83it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.84it/s] 24%|██▍ | 12/50 [00:03<00:09, 3.85it/s] 26%|██▌ | 13/50 [00:03<00:09, 3.85it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.85it/s] 30%|███ | 15/50 [00:03<00:09, 3.85it/s] 32%|███▏ | 16/50 [00:04<00:08, 3.85it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.85it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.84it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.85it/s] 40%|████ | 20/50 [00:05<00:07, 3.85it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.84it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.84it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.84it/s] 48%|████▊ | 24/50 [00:06<00:06, 3.85it/s] 50%|█████ | 25/50 [00:06<00:06, 3.85it/s] 52%|█████▏ | 26/50 [00:06<00:06, 3.85it/s] 54%|█████▍ | 27/50 [00:07<00:05, 3.85it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.85it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.85it/s] 60%|██████ | 30/50 [00:07<00:05, 3.85it/s] 62%|██████▏ | 31/50 [00:08<00:04, 3.85it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.84it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.83it/s] 68%|██████▊ | 34/50 [00:08<00:04, 3.84it/s] 70%|███████ | 35/50 [00:09<00:03, 3.84it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.84it/s] 74%|███████▍ | 37/50 [00:09<00:03, 3.85it/s] 76%|███████▌ | 38/50 [00:09<00:03, 3.84it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.83it/s] 80%|████████ | 40/50 [00:10<00:02, 3.84it/s] 82%|████████▏ | 41/50 [00:10<00:02, 3.84it/s] 84%|████████▍ | 42/50 [00:10<00:02, 3.84it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.84it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.84it/s] 90%|█████████ | 45/50 [00:11<00:01, 3.82it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.83it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.83it/s] 96%|█████████▌| 48/50 [00:12<00:00, 3.84it/s] 98%|█████████▊| 49/50 [00:12<00:00, 3.83it/s] 100%|██████████| 50/50 [00:13<00:00, 3.84it/s] 100%|██████████| 50/50 [00:13<00:00, 3.82it/s]
Prediction
multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2bIDmcmymzy22fewthdw5hpk6mpzfmStatusSucceededSourceWebHardwareT4Total durationCreatedInput
- width
- 512
- height
- 512
- num_outputs
- 1
- guidance_scale
- "6"
- negative_prompt
- 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, artist name
- positive_prompt
- masterpiece, best quality, charming, perfect kitsune girl
- num_inference_steps
- "50"
{ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", { input: { width: 512, height: 512, num_outputs: 1, guidance_scale: "6", negative_prompt: "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, artist name", positive_prompt: "masterpiece, best quality, charming, perfect kitsune girl", num_inference_steps: "50" } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", input={ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run multitrickfox/waifu-diffusion-16bit 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": "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b \ -i 'width=512' \ -i 'height=512' \ -i 'num_outputs=1' \ -i 'guidance_scale="6"' \ -i 'negative_prompt="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, artist name"' \ -i 'positive_prompt="masterpiece, best quality, charming, perfect kitsune girl"' \ -i 'num_inference_steps="50"'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2022-11-03T22:38:20.842849Z", "created_at": "2022-11-03T22:38:06.783468Z", "data_removed": false, "error": null, "id": "mcmymzy22fewthdw5hpk6mpzfm", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" }, "logs": "Using seed: 14792\n\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:15, 3.20it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.56it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.68it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.72it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.73it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.75it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.75it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.75it/s]\n 18%|█▊ | 9/50 [00:02<00:10, 3.75it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.76it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.76it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.76it/s]\n 26%|██▌ | 13/50 [00:03<00:09, 3.75it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.75it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.76it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.76it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.75it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.76it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.76it/s]\n 40%|████ | 20/50 [00:05<00:07, 3.75it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.75it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.74it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.74it/s]\n 48%|████▊ | 24/50 [00:06<00:06, 3.74it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.74it/s]\n 52%|█████▏ | 26/50 [00:06<00:06, 3.73it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.75it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.75it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.75it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.75it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.76it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.76it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.76it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.76it/s]\n 70%|███████ | 35/50 [00:09<00:03, 3.75it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.74it/s]\n 74%|███████▍ | 37/50 [00:09<00:03, 3.75it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.75it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.75it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.75it/s]\n 82%|████████▏ | 41/50 [00:10<00:02, 3.76it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.75it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.75it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.76it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.77it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.77it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.77it/s]\n 96%|█████████▌| 48/50 [00:12<00:00, 3.77it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.77it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.77it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.75it/s]", "metrics": { "predict_time": 14.023962, "total_time": 14.059381 }, "output": [ "https://replicate.delivery/pbxt/BkK0t4YnotpgA95G3psvuVoJqdwoYdcdZZ2DazcuzmE30HfHA/out-0.png" ], "started_at": "2022-11-03T22:38:06.818887Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/mcmymzy22fewthdw5hpk6mpzfm", "cancel": "https://api.replicate.com/v1/predictions/mcmymzy22fewthdw5hpk6mpzfm/cancel" }, "version": "d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b" }
Generated inUsing seed: 14792 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:15, 3.20it/s] 4%|▍ | 2/50 [00:00<00:13, 3.56it/s] 6%|▌ | 3/50 [00:00<00:12, 3.68it/s] 8%|▊ | 4/50 [00:01<00:12, 3.72it/s] 10%|█ | 5/50 [00:01<00:12, 3.73it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.75it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.75it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.75it/s] 18%|█▊ | 9/50 [00:02<00:10, 3.75it/s] 20%|██ | 10/50 [00:02<00:10, 3.76it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.76it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.76it/s] 26%|██▌ | 13/50 [00:03<00:09, 3.75it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.75it/s] 30%|███ | 15/50 [00:04<00:09, 3.76it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.76it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.75it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.76it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.76it/s] 40%|████ | 20/50 [00:05<00:07, 3.75it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.75it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.74it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.74it/s] 48%|████▊ | 24/50 [00:06<00:06, 3.74it/s] 50%|█████ | 25/50 [00:06<00:06, 3.74it/s] 52%|█████▏ | 26/50 [00:06<00:06, 3.73it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.75it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.75it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.75it/s] 60%|██████ | 30/50 [00:08<00:05, 3.75it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.76it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.76it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.76it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.76it/s] 70%|███████ | 35/50 [00:09<00:03, 3.75it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.74it/s] 74%|███████▍ | 37/50 [00:09<00:03, 3.75it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.75it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.75it/s] 80%|████████ | 40/50 [00:10<00:02, 3.75it/s] 82%|████████▏ | 41/50 [00:10<00:02, 3.76it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.75it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.75it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.76it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.77it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.77it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.77it/s] 96%|█████████▌| 48/50 [00:12<00:00, 3.77it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.77it/s] 100%|██████████| 50/50 [00:13<00:00, 3.77it/s] 100%|██████████| 50/50 [00:13<00:00, 3.75it/s]
Prediction
multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2bIDedjrjqcyvferrczscllfjyk7w4StatusSucceededSourceWebHardwareT4Total durationCreatedInput
- width
- 512
- height
- 512
- num_outputs
- 1
- guidance_scale
- "6"
- negative_prompt
- 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, artist name
- positive_prompt
- 1girl, masterpiece, best quality, charming, perfect kitsune girl
- num_inference_steps
- "50"
{ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl, masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", { input: { width: 512, height: 512, num_outputs: 1, guidance_scale: "6", negative_prompt: "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, artist name", positive_prompt: "1girl, masterpiece, best quality, charming, perfect kitsune girl", num_inference_steps: "50" } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", input={ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl, masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run multitrickfox/waifu-diffusion-16bit 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": "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl, masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b \ -i 'width=512' \ -i 'height=512' \ -i 'num_outputs=1' \ -i 'guidance_scale="6"' \ -i 'negative_prompt="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, artist name"' \ -i 'positive_prompt="1girl, masterpiece, best quality, charming, perfect kitsune girl"' \ -i 'num_inference_steps="50"'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl, masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2022-11-04T11:33:12.651967Z", "created_at": "2022-11-04T11:32:58.537308Z", "data_removed": false, "error": null, "id": "edjrjqcyvferrczscllfjyk7w4", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl, masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" }, "logs": "Using seed: 16189\n\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:15, 3.07it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.48it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.63it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.68it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.70it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.71it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.72it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.73it/s]\n 18%|█▊ | 9/50 [00:02<00:10, 3.74it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.75it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.76it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.75it/s]\n 26%|██▌ | 13/50 [00:03<00:09, 3.75it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.74it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.74it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.76it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.76it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.75it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.73it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.73it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.73it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.74it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.74it/s]\n 48%|████▊ | 24/50 [00:06<00:06, 3.73it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.73it/s]\n 52%|█████▏ | 26/50 [00:06<00:06, 3.74it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.75it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.74it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.74it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.73it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.74it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.74it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.74it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.73it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.73it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.74it/s]\n 74%|███████▍ | 37/50 [00:09<00:03, 3.75it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.74it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.74it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.73it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.74it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.76it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.75it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.74it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.74it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.74it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.73it/s]\n 96%|█████████▌| 48/50 [00:12<00:00, 3.74it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.73it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.73it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.73it/s]", "metrics": { "predict_time": 14.073276, "total_time": 14.114659 }, "output": [ "https://replicate.delivery/pbxt/0i7CBehJczQVPq11s3GRfDRezgFg7OUuXqfRF9Ve01iEPVlfD/out-0.png" ], "started_at": "2022-11-04T11:32:58.578691Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/edjrjqcyvferrczscllfjyk7w4", "cancel": "https://api.replicate.com/v1/predictions/edjrjqcyvferrczscllfjyk7w4/cancel" }, "version": "d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b" }
Generated inUsing seed: 16189 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:15, 3.07it/s] 4%|▍ | 2/50 [00:00<00:13, 3.48it/s] 6%|▌ | 3/50 [00:00<00:12, 3.63it/s] 8%|▊ | 4/50 [00:01<00:12, 3.68it/s] 10%|█ | 5/50 [00:01<00:12, 3.70it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.71it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.72it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.73it/s] 18%|█▊ | 9/50 [00:02<00:10, 3.74it/s] 20%|██ | 10/50 [00:02<00:10, 3.75it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.76it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.75it/s] 26%|██▌ | 13/50 [00:03<00:09, 3.75it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.74it/s] 30%|███ | 15/50 [00:04<00:09, 3.74it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.76it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.76it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.75it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.73it/s] 40%|████ | 20/50 [00:05<00:08, 3.73it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.73it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.74it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.74it/s] 48%|████▊ | 24/50 [00:06<00:06, 3.73it/s] 50%|█████ | 25/50 [00:06<00:06, 3.73it/s] 52%|█████▏ | 26/50 [00:06<00:06, 3.74it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.75it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.74it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.74it/s] 60%|██████ | 30/50 [00:08<00:05, 3.73it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.74it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.74it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.74it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.73it/s] 70%|███████ | 35/50 [00:09<00:04, 3.73it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.74it/s] 74%|███████▍ | 37/50 [00:09<00:03, 3.75it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.74it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.74it/s] 80%|████████ | 40/50 [00:10<00:02, 3.73it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.74it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.76it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.75it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.74it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.74it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.74it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.73it/s] 96%|█████████▌| 48/50 [00:12<00:00, 3.74it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.73it/s] 100%|██████████| 50/50 [00:13<00:00, 3.73it/s] 100%|██████████| 50/50 [00:13<00:00, 3.73it/s]
Prediction
multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2bID2bi5iyzewfedvbctbefmy3mauuStatusSucceededSourceWebHardwareT4Total durationCreatedInput
- width
- 512
- height
- 512
- num_outputs
- 1
- guidance_scale
- "6"
- negative_prompt
- 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, artist name
- positive_prompt
- 1girl, masterpiece, best quality, charming, perfect kitsune girl
- num_inference_steps
- "50"
{ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl, masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", { input: { width: 512, height: 512, num_outputs: 1, guidance_scale: "6", negative_prompt: "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, artist name", positive_prompt: "1girl, masterpiece, best quality, charming, perfect kitsune girl", num_inference_steps: "50" } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", input={ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl, masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run multitrickfox/waifu-diffusion-16bit 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": "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl, masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b \ -i 'width=512' \ -i 'height=512' \ -i 'num_outputs=1' \ -i 'guidance_scale="6"' \ -i 'negative_prompt="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, artist name"' \ -i 'positive_prompt="1girl, masterpiece, best quality, charming, perfect kitsune girl"' \ -i 'num_inference_steps="50"'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl, masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2022-11-04T11:33:55.719076Z", "created_at": "2022-11-04T11:33:41.565198Z", "data_removed": false, "error": null, "id": "2bi5iyzewfedvbctbefmy3mauu", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl, masterpiece, best quality, charming, perfect kitsune girl", "num_inference_steps": "50" }, "logs": "Using seed: 1191\n\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:16, 2.92it/s]\n 4%|▍ | 2/50 [00:00<00:14, 3.40it/s]\n 6%|▌ | 3/50 [00:00<00:13, 3.56it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.63it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.66it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.69it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.70it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.71it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.73it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.73it/s]\n 22%|██▏ | 11/50 [00:03<00:10, 3.73it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.73it/s]\n 26%|██▌ | 13/50 [00:03<00:09, 3.75it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.74it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.75it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.75it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.74it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.74it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.74it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.74it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.75it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.74it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.74it/s]\n 48%|████▊ | 24/50 [00:06<00:06, 3.74it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.74it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.74it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.73it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.73it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.73it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.74it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.73it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.71it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.73it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.74it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.73it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.72it/s]\n 74%|███████▍ | 37/50 [00:09<00:03, 3.72it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.73it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.73it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.72it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.72it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.71it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.73it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.71it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.72it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.72it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.72it/s]\n 96%|█████████▌| 48/50 [00:12<00:00, 3.72it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.72it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.73it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.71it/s]", "metrics": { "predict_time": 14.116711, "total_time": 14.153878 }, "output": [ "https://replicate.delivery/pbxt/jFDdH3v2dS73HtutvhArz2QKtqeCShJoRY6Fr9rQlYoRVVePA/out-0.png" ], "started_at": "2022-11-04T11:33:41.602365Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/2bi5iyzewfedvbctbefmy3mauu", "cancel": "https://api.replicate.com/v1/predictions/2bi5iyzewfedvbctbefmy3mauu/cancel" }, "version": "d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b" }
Generated inUsing seed: 1191 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:16, 2.92it/s] 4%|▍ | 2/50 [00:00<00:14, 3.40it/s] 6%|▌ | 3/50 [00:00<00:13, 3.56it/s] 8%|▊ | 4/50 [00:01<00:12, 3.63it/s] 10%|█ | 5/50 [00:01<00:12, 3.66it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.69it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.70it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.71it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.73it/s] 20%|██ | 10/50 [00:02<00:10, 3.73it/s] 22%|██▏ | 11/50 [00:03<00:10, 3.73it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.73it/s] 26%|██▌ | 13/50 [00:03<00:09, 3.75it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.74it/s] 30%|███ | 15/50 [00:04<00:09, 3.75it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.75it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.74it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.74it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.74it/s] 40%|████ | 20/50 [00:05<00:08, 3.74it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.75it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.74it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.74it/s] 48%|████▊ | 24/50 [00:06<00:06, 3.74it/s] 50%|█████ | 25/50 [00:06<00:06, 3.74it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.74it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.73it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.73it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.73it/s] 60%|██████ | 30/50 [00:08<00:05, 3.74it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.73it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.71it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.73it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.74it/s] 70%|███████ | 35/50 [00:09<00:04, 3.73it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.72it/s] 74%|███████▍ | 37/50 [00:09<00:03, 3.72it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.73it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.73it/s] 80%|████████ | 40/50 [00:10<00:02, 3.72it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.72it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.71it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.73it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.71it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.72it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.72it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.72it/s] 96%|█████████▌| 48/50 [00:12<00:00, 3.72it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.72it/s] 100%|██████████| 50/50 [00:13<00:00, 3.73it/s] 100%|██████████| 50/50 [00:13<00:00, 3.71it/s]
Prediction
multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2bIDaccaw2wypbaynkydgojty2p5zqStatusSucceededSourceWebHardwareT4Total durationCreatedInput
- width
- 512
- height
- 512
- num_outputs
- 1
- guidance_scale
- "6"
- negative_prompt
- 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, artist name
- positive_prompt
- 1girl masterpiece best quality charming perfect kitsune girl
- num_inference_steps
- "50"
{ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl masterpiece best quality charming perfect kitsune girl", "num_inference_steps": "50" }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", { input: { width: 512, height: 512, num_outputs: 1, guidance_scale: "6", negative_prompt: "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, artist name", positive_prompt: "1girl masterpiece best quality charming perfect kitsune girl", num_inference_steps: "50" } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", input={ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl masterpiece best quality charming perfect kitsune girl", "num_inference_steps": "50" } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run multitrickfox/waifu-diffusion-16bit 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": "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl masterpiece best quality charming perfect kitsune girl", "num_inference_steps": "50" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b \ -i 'width=512' \ -i 'height=512' \ -i 'num_outputs=1' \ -i 'guidance_scale="6"' \ -i 'negative_prompt="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, artist name"' \ -i 'positive_prompt="1girl masterpiece best quality charming perfect kitsune girl"' \ -i 'num_inference_steps="50"'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl masterpiece best quality charming perfect kitsune girl", "num_inference_steps": "50" } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2022-11-04T11:35:14.396924Z", "created_at": "2022-11-04T11:35:00.075418Z", "data_removed": false, "error": null, "id": "accaw2wypbaynkydgojty2p5zq", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl masterpiece best quality charming perfect kitsune girl", "num_inference_steps": "50" }, "logs": "Using seed: 7468\n\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:15, 3.07it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.43it/s]\n 6%|▌ | 3/50 [00:00<00:13, 3.55it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.62it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.65it/s]\n 12%|█▏ | 6/50 [00:01<00:12, 3.66it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.68it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.70it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.70it/s]\n 22%|██▏ | 11/50 [00:03<00:10, 3.70it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.69it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.69it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.70it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.69it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.69it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.69it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.69it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.69it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.69it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.69it/s]\n 44%|████▍ | 22/50 [00:06<00:07, 3.70it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.69it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.69it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.69it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.68it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.68it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.69it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.69it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.69it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.69it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.69it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.68it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.68it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.69it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.68it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.69it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.69it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.68it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.67it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.67it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.68it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.66it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.67it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.67it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.68it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.67it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.67it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.67it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.66it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.67it/s]", "metrics": { "predict_time": 14.286027, "total_time": 14.321506 }, "output": [ "https://replicate.delivery/pbxt/yofp8BPyk8X8dyBahKF6e0lJIcq2kcxoNfFHppaB0VZkXV5fA/out-0.png" ], "started_at": "2022-11-04T11:35:00.110897Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/accaw2wypbaynkydgojty2p5zq", "cancel": "https://api.replicate.com/v1/predictions/accaw2wypbaynkydgojty2p5zq/cancel" }, "version": "d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b" }
Generated inUsing seed: 7468 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:15, 3.07it/s] 4%|▍ | 2/50 [00:00<00:13, 3.43it/s] 6%|▌ | 3/50 [00:00<00:13, 3.55it/s] 8%|▊ | 4/50 [00:01<00:12, 3.62it/s] 10%|█ | 5/50 [00:01<00:12, 3.65it/s] 12%|█▏ | 6/50 [00:01<00:12, 3.66it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.68it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.69it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.70it/s] 20%|██ | 10/50 [00:02<00:10, 3.70it/s] 22%|██▏ | 11/50 [00:03<00:10, 3.70it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.69it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.69it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.70it/s] 30%|███ | 15/50 [00:04<00:09, 3.69it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.69it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.69it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.69it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.69it/s] 40%|████ | 20/50 [00:05<00:08, 3.69it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.69it/s] 44%|████▍ | 22/50 [00:06<00:07, 3.70it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.69it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.69it/s] 50%|█████ | 25/50 [00:06<00:06, 3.69it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.68it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.68it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.69it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.69it/s] 60%|██████ | 30/50 [00:08<00:05, 3.69it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.69it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.69it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.68it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.68it/s] 70%|███████ | 35/50 [00:09<00:04, 3.69it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.68it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.69it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.69it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.68it/s] 80%|████████ | 40/50 [00:10<00:02, 3.67it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.67it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.68it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.66it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.67it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.67it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.68it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.67it/s] 96%|█████████▌| 48/50 [00:13<00:00, 3.67it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.67it/s] 100%|██████████| 50/50 [00:13<00:00, 3.66it/s] 100%|██████████| 50/50 [00:13<00:00, 3.67it/s]
Prediction
multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2bIDxzqt56wzgfc2xjpx2c4xupthmqStatusSucceededSourceWebHardwareT4Total durationCreatedInput
- width
- 512
- height
- 512
- num_outputs
- 1
- guidance_scale
- "6"
- negative_prompt
- 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, artist name
- positive_prompt
- 1girl looking_at_viewer masterpiece best quality charming perfect kitsune girl
- num_inference_steps
- "50"
{ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl looking_at_viewer masterpiece best quality charming perfect kitsune girl", "num_inference_steps": "50" }
Install Replicate’s Node.js client library:npm install replicate
Import and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", { input: { width: 512, height: 512, num_outputs: 1, guidance_scale: "6", negative_prompt: "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, artist name", positive_prompt: "1girl looking_at_viewer masterpiece best quality charming perfect kitsune girl", num_inference_steps: "50" } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run multitrickfox/waifu-diffusion-16bit using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", input={ "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl looking_at_viewer masterpiece best quality charming perfect kitsune girl", "num_inference_steps": "50" } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
Run multitrickfox/waifu-diffusion-16bit 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": "multitrickfox/waifu-diffusion-16bit:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl looking_at_viewer masterpiece best quality charming perfect kitsune girl", "num_inference_steps": "50" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cog
If you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b \ -i 'width=512' \ -i 'height=512' \ -i 'num_outputs=1' \ -i 'guidance_scale="6"' \ -i 'negative_prompt="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, artist name"' \ -i 'positive_prompt="1girl looking_at_viewer masterpiece best quality charming perfect kitsune girl"' \ -i 'num_inference_steps="50"'
To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/multitrickfox/waifu-diffusion-16bit@sha256:d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl looking_at_viewer masterpiece best quality charming perfect kitsune girl", "num_inference_steps": "50" } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2022-11-04T11:38:33.214446Z", "created_at": "2022-11-04T11:38:19.123776Z", "data_removed": false, "error": null, "id": "xzqt56wzgfc2xjpx2c4xupthmq", "input": { "width": 512, "height": 512, "num_outputs": 1, "guidance_scale": "6", "negative_prompt": "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, artist name", "positive_prompt": "1girl looking_at_viewer masterpiece best quality charming perfect kitsune girl", "num_inference_steps": "50" }, "logs": "Using seed: 10752\n\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:15, 3.12it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.49it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.62it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.68it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.70it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.73it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.74it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.76it/s]\n 18%|█▊ | 9/50 [00:02<00:10, 3.76it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.76it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.77it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.77it/s]\n 26%|██▌ | 13/50 [00:03<00:09, 3.76it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.75it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.75it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.76it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.74it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.74it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.73it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.74it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.75it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.75it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.74it/s]\n 48%|████▊ | 24/50 [00:06<00:06, 3.74it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.74it/s]\n 52%|█████▏ | 26/50 [00:06<00:06, 3.75it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.75it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.75it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.75it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.74it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.73it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.74it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.74it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.75it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.74it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.73it/s]\n 74%|███████▍ | 37/50 [00:09<00:03, 3.73it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.74it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.74it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.73it/s]\n 82%|████████▏ | 41/50 [00:10<00:02, 3.72it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.73it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.74it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.74it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.73it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.73it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.74it/s]\n 96%|█████████▌| 48/50 [00:12<00:00, 3.74it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.74it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.73it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.73it/s]", "metrics": { "predict_time": 14.054955, "total_time": 14.09067 }, "output": [ "https://replicate.delivery/pbxt/yygjcwydsSqCJxvc5hYEbJ86LWFHKUQrQ01XTBRKCzaurKfHA/out-0.png" ], "started_at": "2022-11-04T11:38:19.159491Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/xzqt56wzgfc2xjpx2c4xupthmq", "cancel": "https://api.replicate.com/v1/predictions/xzqt56wzgfc2xjpx2c4xupthmq/cancel" }, "version": "d908d47fa301ffe59dce52588e0603add72bfcbc4bb3f78b4516cac541ba7b2b" }
Generated inUsing seed: 10752 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:15, 3.12it/s] 4%|▍ | 2/50 [00:00<00:13, 3.49it/s] 6%|▌ | 3/50 [00:00<00:12, 3.62it/s] 8%|▊ | 4/50 [00:01<00:12, 3.68it/s] 10%|█ | 5/50 [00:01<00:12, 3.70it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.73it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.74it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.76it/s] 18%|█▊ | 9/50 [00:02<00:10, 3.76it/s] 20%|██ | 10/50 [00:02<00:10, 3.76it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.77it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.77it/s] 26%|██▌ | 13/50 [00:03<00:09, 3.76it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.75it/s] 30%|███ | 15/50 [00:04<00:09, 3.75it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.76it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.74it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.74it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.73it/s] 40%|████ | 20/50 [00:05<00:08, 3.74it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.75it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.75it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.74it/s] 48%|████▊ | 24/50 [00:06<00:06, 3.74it/s] 50%|█████ | 25/50 [00:06<00:06, 3.74it/s] 52%|█████▏ | 26/50 [00:06<00:06, 3.75it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.75it/s] 56%|█████▌ | 28/50 [00:07<00:05, 3.75it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.75it/s] 60%|██████ | 30/50 [00:08<00:05, 3.74it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.73it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.74it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.74it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.75it/s] 70%|███████ | 35/50 [00:09<00:04, 3.74it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.73it/s] 74%|███████▍ | 37/50 [00:09<00:03, 3.73it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.74it/s] 78%|███████▊ | 39/50 [00:10<00:02, 3.74it/s] 80%|████████ | 40/50 [00:10<00:02, 3.73it/s] 82%|████████▏ | 41/50 [00:10<00:02, 3.72it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.73it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.74it/s] 88%|████████▊ | 44/50 [00:11<00:01, 3.74it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.73it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.73it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.74it/s] 96%|█████████▌| 48/50 [00:12<00:00, 3.74it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.74it/s] 100%|██████████| 50/50 [00:13<00:00, 3.73it/s] 100%|██████████| 50/50 [00:13<00:00, 3.73it/s]
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