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A frankensteinian amalgamation of notebooks, models and techniques for the generation of AI Art and Animations.
This code is built on Discoart.
nightmareai
/
disco-diffusion
Generate images using a variety of techniques - Powered by Discoart
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=nightmareai/disco-diffusion
or set up a project from scratch
Install Replicate’s Node.js client library:
npm install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run nightmareai/disco-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"nightmareai/disco-diffusion:3c128f652e9f24e72896ac0b019e47facfd6bccf93104d50f09f1f2196325507",
{
input: {
RN50: true,
RN101: false,
steps: 250,
width: 1280,
RN50x4: false,
ViTB16: true,
ViTB32: true,
ViTL14: false,
height: 768,
prompt: "A beautiful painting of a singular lighthouse, shining its light across a tumultuous sea of blood by greg rutkowski and thomas kinkade, Trending on artstation.",
RN50x16: false,
RN50x64: false,
RN50x101: false,
tv_scale: 0,
sat_scale: 0,
skip_augs: false,
RN50_cc12m: false,
ViTL14_336: false,
init_scale: 1000,
skip_steps: 10,
range_scale: 150,
cutn_batches: 4,
display_rate: 20,
target_scale: 20000,
RN101_yfcc15m: false,
RN50_yffcc15m: false,
diffusion_model: "512x512_diffusion_uncond_finetune_008100",
ViTB32_laion2b_e16: false,
clip_guidance_scale: 5000,
use_secondary_model: true,
RN50_quickgelu_cc12m: false,
ViTB16_laion400m_e31: false,
ViTB16_laion400m_e32: false,
ViTB32_laion400m_e31: false,
ViTB32_laion400m_e32: false,
RN50_quickgelu_yfcc15m: false,
RN101_quickgelu_yfcc15m: false,
diffusion_sampling_mode: "ddim",
ViTB32quickgelu_laion400m_e31: false,
ViTB32quickgelu_laion400m_e32: false
}
}
);
console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:
pip install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:
import replicateRun nightmareai/disco-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"nightmareai/disco-diffusion:3c128f652e9f24e72896ac0b019e47facfd6bccf93104d50f09f1f2196325507",
input={
"RN50": True,
"RN101": False,
"steps": 250,
"width": 1280,
"RN50x4": False,
"ViTB16": True,
"ViTB32": True,
"ViTL14": False,
"height": 768,
"prompt": "A beautiful painting of a singular lighthouse, shining its light across a tumultuous sea of blood by greg rutkowski and thomas kinkade, Trending on artstation.",
"RN50x16": False,
"RN50x64": False,
"RN50x101": False,
"tv_scale": 0,
"sat_scale": 0,
"skip_augs": False,
"RN50_cc12m": False,
"ViTL14_336": False,
"init_scale": 1000,
"skip_steps": 10,
"range_scale": 150,
"cutn_batches": 4,
"display_rate": 20,
"target_scale": 20000,
"RN101_yfcc15m": False,
"RN50_yffcc15m": False,
"diffusion_model": "512x512_diffusion_uncond_finetune_008100",
"ViTB32_laion2b_e16": False,
"clip_guidance_scale": 5000,
"use_secondary_model": True,
"RN50_quickgelu_cc12m": False,
"ViTB16_laion400m_e31": False,
"ViTB16_laion400m_e32": False,
"ViTB32_laion400m_e31": False,
"ViTB32_laion400m_e32": False,
"RN50_quickgelu_yfcc15m": False,
"RN101_quickgelu_yfcc15m": False,
"diffusion_sampling_mode": "ddim",
"ViTB32quickgelu_laion400m_e31": False,
"ViTB32quickgelu_laion400m_e32": False
}
)
# The nightmareai/disco-diffusion model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
# https://replicate.com/nightmareai/disco-diffusion/api#output-schema
print(item)To learn more, take a look at the guide on getting started with Python.
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run nightmareai/disco-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": "3c128f652e9f24e72896ac0b019e47facfd6bccf93104d50f09f1f2196325507",
"input": {
"RN50": true,
"RN101": false,
"steps": 250,
"width": 1280,
"RN50x4": false,
"ViTB16": true,
"ViTB32": true,
"ViTL14": false,
"height": 768,
"prompt": "A beautiful painting of a singular lighthouse, shining its light across a tumultuous sea of blood by greg rutkowski and thomas kinkade, Trending on artstation.",
"RN50x16": false,
"RN50x64": false,
"RN50x101": false,
"tv_scale": 0,
"sat_scale": 0,
"skip_augs": false,
"RN50_cc12m": false,
"ViTL14_336": false,
"init_scale": 1000,
"skip_steps": 10,
"range_scale": 150,
"cutn_batches": 4,
"display_rate": 20,
"target_scale": 20000,
"RN101_yfcc15m": false,
"RN50_yffcc15m": false,
"diffusion_model": "512x512_diffusion_uncond_finetune_008100",
"ViTB32_laion2b_e16": false,
"clip_guidance_scale": 5000,
"use_secondary_model": true,
"RN50_quickgelu_cc12m": false,
"ViTB16_laion400m_e31": false,
"ViTB16_laion400m_e32": false,
"ViTB32_laion400m_e31": false,
"ViTB32_laion400m_e32": false,
"RN50_quickgelu_yfcc15m": false,
"RN101_quickgelu_yfcc15m": false,
"diffusion_sampling_mode": "ddim",
"ViTB32quickgelu_laion400m_e31": false,
"ViTB32quickgelu_laion400m_e32": false
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:
brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/nightmareai/disco-diffusion@sha256:3c128f652e9f24e72896ac0b019e47facfd6bccf93104d50f09f1f2196325507 \
-i 'RN50=true' \
-i 'RN101=false' \
-i 'steps=250' \
-i 'width=1280' \
-i 'RN50x4=false' \
-i 'ViTB16=true' \
-i 'ViTB32=true' \
-i 'ViTL14=false' \
-i 'height=768' \
-i 'prompt="A beautiful painting of a singular lighthouse, shining its light across a tumultuous sea of blood by greg rutkowski and thomas kinkade, Trending on artstation."' \
-i 'RN50x16=false' \
-i 'RN50x64=false' \
-i 'RN50x101=false' \
-i 'tv_scale=0' \
-i 'sat_scale=0' \
-i 'skip_augs=false' \
-i 'RN50_cc12m=false' \
-i 'ViTL14_336=false' \
-i 'init_scale=1000' \
-i 'skip_steps=10' \
-i 'range_scale=150' \
-i 'cutn_batches=4' \
-i 'display_rate=20' \
-i 'target_scale=20000' \
-i 'RN101_yfcc15m=false' \
-i 'RN50_yffcc15m=false' \
-i 'diffusion_model="512x512_diffusion_uncond_finetune_008100"' \
-i 'ViTB32_laion2b_e16=false' \
-i 'clip_guidance_scale=5000' \
-i 'use_secondary_model=true' \
-i 'RN50_quickgelu_cc12m=false' \
-i 'ViTB16_laion400m_e31=false' \
-i 'ViTB16_laion400m_e32=false' \
-i 'ViTB32_laion400m_e31=false' \
-i 'ViTB32_laion400m_e32=false' \
-i 'RN50_quickgelu_yfcc15m=false' \
-i 'RN101_quickgelu_yfcc15m=false' \
-i 'diffusion_sampling_mode="ddim"' \
-i 'ViTB32quickgelu_laion400m_e31=false' \
-i 'ViTB32quickgelu_laion400m_e32=false'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/nightmareai/disco-diffusion@sha256:3c128f652e9f24e72896ac0b019e47facfd6bccf93104d50f09f1f2196325507curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "RN50": true, "RN101": false, "steps": 250, "width": 1280, "RN50x4": false, "ViTB16": true, "ViTB32": true, "ViTL14": false, "height": 768, "prompt": "A beautiful painting of a singular lighthouse, shining its light across a tumultuous sea of blood by greg rutkowski and thomas kinkade, Trending on artstation.", "RN50x16": false, "RN50x64": false, "RN50x101": false, "tv_scale": 0, "sat_scale": 0, "skip_augs": false, "RN50_cc12m": false, "ViTL14_336": false, "init_scale": 1000, "skip_steps": 10, "range_scale": 150, "cutn_batches": 4, "display_rate": 20, "target_scale": 20000, "RN101_yfcc15m": false, "RN50_yffcc15m": false, "diffusion_model": "512x512_diffusion_uncond_finetune_008100", "ViTB32_laion2b_e16": false, "clip_guidance_scale": 5000, "use_secondary_model": true, "RN50_quickgelu_cc12m": false, "ViTB16_laion400m_e31": false, "ViTB16_laion400m_e32": false, "ViTB32_laion400m_e31": false, "ViTB32_laion400m_e32": false, "RN50_quickgelu_yfcc15m": false, "RN101_quickgelu_yfcc15m": false, "diffusion_sampling_mode": "ddim", "ViTB32quickgelu_laion400m_e31": false, "ViTB32quickgelu_laion400m_e32": false } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Add a payment method to run this model.
Each run costs approximately $1.05. Alternatively, try out our featured models for free.
Sign in with GitHub
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Output
{
"completed_at": "2022-07-10T11:17:36.820113Z",
"created_at": "2022-07-10T11:00:26.481418Z",
"data_removed": false,
"error": null,
"id": "bzp5mhiyarcmvoinbxpubjhzou",
"input": {
"RN50": true,
"steps": 250,
"width": 1280,
"ViTB16": true,
"ViTB32": true,
"height": 768,
"prompt": "A beautiful painting of a singular lighthouse, shining its light across a tumultuous sea of blood by greg rutkowski and thomas kinkade, Trending on artstation.",
"init_scale": 1000,
"skip_steps": 10,
"range_scale": 150,
"cutn_batches": 4,
"display_rate": 20,
"target_scale": 20000,
"diffusion_model": "512x512_diffusion_uncond_finetune_008100",
"clip_guidance_scale": 5000,
"use_secondary_model": true,
"diffusion_sampling_mode": "ddim"
},
"logs": "2022-07-10 11:00:26.617 | INFO | dd:start_run:2224 - 💼 1 jobs found.\n2022-07-10 11:00:26.618 | INFO | dd:start_run:2236 - ⚒️ Session 0ed00f4d-91e7-4ca9-acff-88072c74069e started...\n2022-07-10 11:00:26.619 | INFO | dd:start_run:2239 - 💼 Processing job 1 of 1...\n2022-07-10 11:00:26.619 | INFO | dd:start_run:2242 - 🌲 Setting TORCH_HOME environment variable to /root/.cache/disco-diffusion...\n2022-07-10 11:00:26.619 | INFO | dd:processBatch:2329 - 🌱 Randomly using seed: 2866669839\n2022-07-10 11:00:26.620 | INFO | dd:free_mem:71 - Clearing CUDA cache on cuda:0...\n2022-07-10 11:00:26.620 | INFO | dd:do_run:1190 - 💻 Starting Run: ba70ca3b-8ed1-4ac4-a09f-3cc046dd3dea(0) at frame 0\n2022-07-10 11:00:26.620 | INFO | dd:clipLoad:1182 - 🤖 Loading model 'ViT-B/32'...\n2022-07-10 11:00:31.138 | INFO | dd:clipLoad:1182 - 🤖 Loading model 'ViT-B/16'...\n2022-07-10 11:00:35.131 | INFO | dd:clipLoad:1182 - 🤖 Loading model 'RN50'...\n2022-07-10 11:00:38.346 | INFO | dd:do_run:1216 - 🤖 Loading secondary model...\n2022-07-10 11:00:38.634 | INFO | dd:do_run:1222 - 🤖 Loading LPIPS...\n/root/.pyenv/versions/3.8.13/lib/python3.8/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and will be removed in 0.15, please use 'weights' instead.\n warnings.warn(\n/root/.pyenv/versions/3.8.13/lib/python3.8/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and will be removed in 0.15. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.\n warnings.warn(msg)\n\u001b[2K\n2022-07-10 11:00:42.292 | INFO | dd:disco:1502 - timestep_respacing : ddim250 | diffusion_steps: 1000\n2022-07-10 11:00:42.293 | INFO | dd:prepModels:1054 - Prepping models...\n2022-07-10 11:00:55.511 | INFO | dd:disco:1532 - Running job '854105ed-bc42-4cf6-a569-59bf14495d4e'...\n2022-07-10 11:00:55.511 | INFO | dd:disco:1545 - 🌱 Seed used: 2866669839\n2022-07-10 11:00:55.513 | INFO | dd:disco:1571 - Frame 0 📝 Prompt: ['A beautiful painting of a singular lighthouse, shining its light across a tumultuous sea of blood by greg rutkowski and thomas kinkade, Trending on artstation.']\n\u001b[2K\n\u001b[2K\n\u001b[2K\nBatches: 0%| | 0/1 [00:00<?, ?it/s]\nOutput()\n2022-07-10 11:00:55.578 | INFO | dd:free_mem:71 - Clearing CUDA cache on cuda:0...\n\n\n 0%| | 0/240 [00:00<?, ?it/s]\u001b[A\nBatch 0, step 0, output 0:\n\n\n\u001b[A\n\n\u001b[2K\n\u001b[2K\n<PIL.Image.Image image 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'/src/images_out/ba70ca3b-8ed1-4ac4-a09f-3cc046dd3dea/ba70ca3b-8ed1-4ac4-a09f-3cc046dd3dea(0)_0.png'\n\n\n100%|██████████| 240/240 [16:35<00:00, 4.50s/it]\u001b[A\n100%|██████████| 240/240 [16:35<00:00, 4.15s/it]\n2022-07-10 11:17:31.558 | INFO | dd:free_mem:71 - Clearing CUDA cache on cuda:0...\n2022-07-10 11:17:31.558 | SUCCESS | dd:start_run:2245 - ✅ Session 0ed00f4d-91e7-4ca9-acff-88072c74069e finished by user.\n2022-07-10 11:17:31.558 | DEBUG | dd:sendSMS:2530 - Not sending SMS\n2022-07-10 11:17:31.558 | INFO | dd:free_mem:71 - Clearing CUDA cache on cuda:0...",
"metrics": {
"predict_time": 1030.13119,
"total_time": 1030.338695
},
"output": [
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}Generated in
2022-07-10 11:00:26.617 | INFO | dd:start_run:2224 - 💼 1 jobs found.
2022-07-10 11:00:26.618 | INFO | dd:start_run:2236 - ⚒️ Session 0ed00f4d-91e7-4ca9-acff-88072c74069e started...
2022-07-10 11:00:26.619 | INFO | dd:start_run:2239 - 💼 Processing job 1 of 1...
2022-07-10 11:00:26.619 | INFO | dd:start_run:2242 - 🌲 Setting TORCH_HOME environment variable to /root/.cache/disco-diffusion...
2022-07-10 11:00:26.619 | INFO | dd:processBatch:2329 - 🌱 Randomly using seed: 2866669839
2022-07-10 11:00:26.620 | INFO | dd:free_mem:71 - Clearing CUDA cache on cuda:0...
2022-07-10 11:00:26.620 | INFO | dd:do_run:1190 - 💻 Starting Run: ba70ca3b-8ed1-4ac4-a09f-3cc046dd3dea(0) at frame 0
2022-07-10 11:00:26.620 | INFO | dd:clipLoad:1182 - 🤖 Loading model 'ViT-B/32'...
2022-07-10 11:00:31.138 | INFO | dd:clipLoad:1182 - 🤖 Loading model 'ViT-B/16'...
2022-07-10 11:00:35.131 | INFO | dd:clipLoad:1182 - 🤖 Loading model 'RN50'...
2022-07-10 11:00:38.346 | INFO | dd:do_run:1216 - 🤖 Loading secondary model...
2022-07-10 11:00:38.634 | INFO | dd:do_run:1222 - 🤖 Loading LPIPS...
/root/.pyenv/versions/3.8.13/lib/python3.8/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and will be removed in 0.15, please use 'weights' instead.
warnings.warn(
/root/.pyenv/versions/3.8.13/lib/python3.8/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and will be removed in 0.15. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.
warnings.warn(msg)
2022-07-10 11:00:42.292 | INFO | dd:disco:1502 - timestep_respacing : ddim250 | diffusion_steps: 1000
2022-07-10 11:00:42.293 | INFO | dd:prepModels:1054 - Prepping models...
2022-07-10 11:00:55.511 | INFO | dd:disco:1532 - Running job '854105ed-bc42-4cf6-a569-59bf14495d4e'...
2022-07-10 11:00:55.511 | INFO | dd:disco:1545 - 🌱 Seed used: 2866669839
2022-07-10 11:00:55.513 | INFO | dd:disco:1571 - Frame 0 📝 Prompt: ['A beautiful painting of a singular lighthouse, shining its light across a tumultuous sea of blood by greg rutkowski and thomas kinkade, Trending on artstation.']
Batches: 0%| | 0/1 [00:00<?, ?it/s]
Output()
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Batch 0, step 120, output 0:
<PIL.Image.Image image mode=RGB size=1280x768 at 0x7F4BB3D99CA0>
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Batch 0, step 140, output 0:
<PIL.Image.Image image mode=RGB size=1280x768 at 0x7F4BB3D99820>
58%|█████▊ | 140/240 [09:34<07:00, 4.21s/it]
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Batch 0, step 160, output 0:
<PIL.Image.Image image mode=RGB size=1280x768 at 0x7F4BB3D99340>
67%|██████▋ | 160/240 [10:59<05:38, 4.23s/it]
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Batch 0, step 180, output 0:
<PIL.Image.Image image mode=RGB size=1280x768 at 0x7F4BB3D99D90>
75%|███████▌ | 180/240 [12:24<04:13, 4.22s/it]
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Batch 0, step 200, output 0:
<PIL.Image.Image image mode=RGB size=1280x768 at 0x7F4BB3D99B80>
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Batch 0, step 220, output 0:
<PIL.Image.Image image mode=RGB size=1280x768 at 0x7F4BB3D99C40>
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Batch 0, step 239, output 0:
<PIL.Image.Image image mode=RGB size=1280x768 at 0x7F4BB3D996A0>
100%|█████████▉| 239/240 [16:35<00:04, 4.23s/it]2022-07-10 11:17:31.125 | INFO | dd:disco:1820 - Image render completed.
2022-07-10 11:17:31.557 | INFO | dd:disco:1840 - Image saved to '/src/images_out/ba70ca3b-8ed1-4ac4-a09f-3cc046dd3dea/ba70ca3b-8ed1-4ac4-a09f-3cc046dd3dea(0)_0.png'
100%|██████████| 240/240 [16:35<00:00, 4.50s/it]
100%|██████████| 240/240 [16:35<00:00, 4.15s/it]
2022-07-10 11:17:31.558 | INFO | dd:free_mem:71 - Clearing CUDA cache on cuda:0...
2022-07-10 11:17:31.558 | SUCCESS | dd:start_run:2245 - ✅ Session 0ed00f4d-91e7-4ca9-acff-88072c74069e finished by user.
2022-07-10 11:17:31.558 | DEBUG | dd:sendSMS:2530 - Not sending SMS
2022-07-10 11:17:31.558 | INFO | dd:free_mem:71 - Clearing CUDA cache on cuda:0...This example was created by a different version, nightmareai/disco-diffusion:bc788225.
Examples
Run time and cost
This model costs approximately $1.05 to run on Replicate, or 0 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.
This model runs on Nvidia A100 (80GB) GPU hardware. Predictions typically complete within 13 minutes. The predict time for this model varies significantly based on the inputs.