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Submission: On December 07 via api from US — Scanned from US
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<div class="flex-1 overflow-ellipsis truncate">
<div class="relative h-full"><input type="text" name="prompt" placeholder="Type your prompt here" class="w-full h-full bg-transparent text-sm lg:text-base border-0 p-3 focus:ring-0 overflow-ellipsis truncate"
value="Clown fish swimming in a coral reef, beautiful, 8k, perfect, award winning, national geographic"></div>
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RUN AI
WITH AN API.
Run and fine-tune open-source models. Deploy custom models at scale. All with
one line of code.
With Replicate you can
Generate imagesGenerate textGenerate videosGenerate musicGenerate speechFine
tune modelsRestore images
stability-ai/sdxl
A text-to-image generative AI model that creates beautiful images
24M runs
stability-ai/sdxl
A text-to-image generative AI model that creates beautiful images
24M runs
ai-forever/kandinsky-2.2
multilingual text2image latent diffusion model
6M runs
ai-forever/kandinsky-2.2
multilingual text2image latent diffusion model
6M runs
stability-ai/stable-diffusion
A latent text-to-image diffusion model capable of generating photo-realistic
images given any text input
105M runs
stability-ai/stable-diffusion
A latent text-to-image diffusion model capable of generating photo-realistic
images given any text input
105M runs
fofr/latent-consistency-model
Super-fast, 0.6s per image. LCM with img2img, large batching and canny
controlnet
128K runs
fofr/latent-consistency-model
Super-fast, 0.6s per image. LCM with img2img, large batching and canny
controlnet
128K runs
meta/llama-2-70b-chat
A 70 billion parameter language model from Meta, fine tuned for chat completions
3M runs
meta/llama-2-70b-chat
A 70 billion parameter language model from Meta, fine tuned for chat completions
3M runs
mistralai/mistral-7b-instruct-v0.1
An instruction-tuned 7 billion parameter language model from Mistral
281K runs
mistralai/mistral-7b-instruct-v0.1
An instruction-tuned 7 billion parameter language model from Mistral
281K runs
meta/codellama-13b
A 13 billion parameter Llama tuned for code completion
73K runs
meta/codellama-13b
A 13 billion parameter Llama tuned for code completion
73K runs
stability-ai/stable-video-diffusion
SVD is a research-only image to video model
216K runs
stability-ai/stable-video-diffusion
SVD is a research-only image to video model
216K runs
anotherjesse/zeroscope-v2-xl
Zeroscope V2 XL & 576w
181K runs
anotherjesse/zeroscope-v2-xl
Zeroscope V2 XL & 576w
181K runs
lucataco/animate-diff
Animate Your Personalized Text-to-Image Diffusion Models
113K runs
lucataco/animate-diff
Animate Your Personalized Text-to-Image Diffusion Models
113K runs
meta/musicgen
Generate music from a prompt or melody
866K runs
meta/musicgen
Generate music from a prompt or melody
866K runs
riffusion/riffusion
Stable diffusion for real-time music generation
828K runs
riffusion/riffusion
Stable diffusion for real-time music generation
828K runs
adirik/styletts2
Generates speech from text
3K runs
adirik/styletts2
Generates speech from text
3K runs
lucataco/xtts-v2
Coqui XTTS-v2: Multilingual Text To Speech Voice Cloning
8K runs
lucataco/xtts-v2
Coqui XTTS-v2: Multilingual Text To Speech Voice Cloning
8K runs
suno-ai/bark
🔊 Text-Prompted Generative Audio Model
174K runs
suno-ai/bark
🔊 Text-Prompted Generative Audio Model
174K runs
fofr/sdxl-emoji
An SDXL fine-tune based on Apple Emojis
2M runs
fofr/sdxl-emoji
An SDXL fine-tune based on Apple Emojis
2M runs
doriandarko/sdxl-hiroshinagai
SDXL model trained on Hiroshi Nagai's illustrations.
5K runs
doriandarko/sdxl-hiroshinagai
SDXL model trained on Hiroshi Nagai's illustrations.
5K runs
fofr/musicgen-choral
MusicGen fine-tuned on chamber choir music
286 runs
fofr/musicgen-choral
MusicGen fine-tuned on chamber choir music
286 runs
tencentarc/gfpgan
Practical face restoration algorithm for *old photos* or *AI-generated faces*
60M runs
tencentarc/gfpgan
Practical face restoration algorithm for *old photos* or *AI-generated faces*
60M runs
nightmareai/real-esrgan
Real-ESRGAN with optional face correction and adjustable upscale
30M runs
nightmareai/real-esrgan
Real-ESRGAN with optional face correction and adjustable upscale
30M runs
Run model
PythonJavaScriptcURL
import replicate
output = replicate.run(
"anotherjesse/zeroscope-v2-xl:9f747673945c62801b13b84701c783929c0ee784e4748ec062204894dda1a351",
input={
"prompt": "Clown fish swimming in a coral reef, beautiful, 8k, perfect, award winning, national geographic"
}
)
print(output)
import Replicate from "replicate";
const replicate = new Replicate();
const output = await replicate.run(
"anotherjesse/zeroscope-v2-xl:9f747673945c62801b13b84701c783929c0ee784e4748ec062204894dda1a351",
{
input: {
prompt: "Clown fish swimming in a coral reef, beautiful, 8k, perfect, award winning, national geographic"
}
}
);
console.log(output);
curl -s -X POST \
-H "Authorization: Token $REPLICATE_API_TOKEN" \
-H "Content-Type: application/json" \
-d $'{
"version": "9f747673945c62801b13b84701c783929c0ee784e4748ec062204894dda1a351",
"input": {
"prompt": "Clown fish swimming in a coral reef, beautiful, 8k, perfect, award winning, national geographic"
}
}' \
https://api.replicate.com/v1/predictions
Run anotherjesse/zeroscope-v2-xl with an API
THOUSANDS OF MODELS CONTRIBUTED BY OUR COMMUNITY
All the latest open-source models are on Replicate. They’re not just demos —
they all actually work and have production-ready APIs.
AI shouldn’t be locked up inside academic papers and demos. Make it real by
pushing it to Replicate.
Explore models
Push a model
meta/llama-2-7b-chat
A 7 billion parameter language model from Meta, fine tuned for chat completions
2M runs
stability-ai/stable-diffusion-inpainting
Fill in masked parts of images with Stable Diffusion
16M runs
microsoft/bringing-old-photos-back-to-life
Bringing Old Photos Back to Life
756K runs
google-research/maxim
Multi-Axis MLP for Image Processing
318K runs
salesforce/blip
Bootstrapping Language-Image Pre-training
57M runs
mistralai/mistral-7b-v0.1
A 7 billion parameter language model from Mistral.
77K runs
meta/llama-2-7b-chat
A 7 billion parameter language model from Meta, fine tuned for chat completions
2M runs
stability-ai/stable-diffusion-inpainting
Fill in masked parts of images with Stable Diffusion
16M runs
microsoft/bringing-old-photos-back-to-life
Bringing Old Photos Back to Life
756K runs
google-research/maxim
Multi-Axis MLP for Image Processing
318K runs
salesforce/blip
Bootstrapping Language-Image Pre-training
57M runs
mistralai/mistral-7b-v0.1
A 7 billion parameter language model from Mistral.
77K runs
laion-ai/erlich
Generate a logo using text.
331K runs
batouresearch/photorealistic-fx
RunDiffusion FX Photorealistic model, developed by RunDiffusion.
38K runs
pollinations/3d-photo-inpainting
3D Photography using Context-aware Layered Depth Inpainting
5K runs
pollinations/modnet
A deep learning approach to remove background & adding new background image
466K runs
prompthero/dreamshaper
Generate a new image given any input text with Dreamshaper v7
160K runs
laion-ai/erlich
Generate a logo using text.
331K runs
batouresearch/photorealistic-fx
RunDiffusion FX Photorealistic model, developed by RunDiffusion.
38K runs
pollinations/3d-photo-inpainting
3D Photography using Context-aware Layered Depth Inpainting
5K runs
pollinations/modnet
A deep learning approach to remove background & adding new background image
466K runs
prompthero/dreamshaper
Generate a new image given any input text with Dreamshaper v7
160K runs
HOW IT WORKS
You can get started with any open-source model with just one line of code. But
as you do more complex things, you fine-tune models or deploy your own custom
code.
RUN OPEN-SOURCE MODELS
Our community has already published thousands of models that are ready to use in
production. You can run these with one line of code.
Explore models
import replicate
output = replicate.run(
"stability-ai/sdxl:39ed52f2a78e934b3ba6e2a89f5b1c712de7dfea535525255b1aa35c5565e08b",
input={
"width": 768,
"height": 768,
"prompt": "An astronaut riding a rainbow unicorn, cinematic, dramatic",
"refine": "expert_ensemble_refiner",
"scheduler": "K_EULER",
}
)
print(output)
FINE-TUNE MODELS WITH YOUR OWN DATA
You can improve open-source models with your own data to create new models that
are better suited to specific tasks.
Image models like SDXL can generate images of a particular person, object, or
style.
Fine-tune image models
Language models like Llama 2 generate text in a specific style or get better at
a particular task.
Fine-tune language models
Train a model:
import replicate
training = replicate.trainings.create(
version="stability-ai/sdxl:c221b2b8ef527988fb59bf24a8b97c4561f1c671f73bd389f866bfb27c061316",
input={
"input_images": "https://my-domain/my-input-images.zip",
},
destination="mattrothenberg/sdxl-fine-tuned"
)
print(training)
This will result in a new model:
mattrothenberg/sdxl-fine-tuned
A very special, fine-tuned version of SDXL
0 runs
mattrothenberg/sdxl-fine-tuned
A very special, fine-tuned version of SDXL
0 runs
Then, you can run it with one line of code:
output = replicate.run(
"mattrothenberg/sdxl-fine-tuned:abcde1234...",
input={"prompt": "a photo of TOK riding a rainbow unicorn"},
)
DEPLOY CUSTOM MODELS
You aren’t limited to the models on Replicate: you can deploy your own custom
models using Cog, our open-source tool for packaging machine learning models.
Cog takes care of generating an API server and deploying it on a big cluster in
the cloud. We scale up and down to handle demand, and you only pay for the
compute that you use.
Learn more
First, define the environment your model runs in with cog.yaml:
build:
gpu: true
system_packages:
- "libgl1-mesa-glx"
- "libglib2.0-0"
python_version: "3.10"
python_packages:
- "torch==1.13.1"
predict: "predict.py:Predictor"
Next, define how predictions are run on your model with predict.py:
from cog import BasePredictor, Input, Path
import torch
class Predictor(BasePredictor):
def setup(self):
"""Load the model into memory to make running multiple predictions efficient"""
self.model = torch.load("./weights.pth")
# The arguments and types the model takes as input
def predict(self,
image: Path = Input(description="Grayscale input image")
) -> Path:
"""Run a single prediction on the model"""
processed_image = preprocess(image)
output = self.model(processed_image)
return postprocess(output)
SCALE ON REPLICATE
Thousands of businesses are building their AI products on Replicate. Your team
can deploy an AI feature in a day and scale to millions of users, without having
to be machine learning experts.
AUTOMATIC SCALE
If you get a ton of traffic, Replicate scales up automatically to handle the
demand. If you don't get any traffic, we scale down to zero and don't charge you
a thing.
* CPU $0.000100/sec
* Nvidia T4 GPU $0.000225/sec
* Nvidia A40 GPU $0.000575/sec
* Nvidia A40 (Large) GPU $0.000725/sec
* Nvidia A100 (40GB) GPU $0.001150/sec
* Nvidia A100 (80GB) GPU $0.001400/sec
* 8x Nvidia A40 (Large) GPU $0.005800/sec
* Learn more about pricing
PAY FOR WHAT YOU USE
Replicate only bills you for how long your code is running. You don't pay for
expensive GPUs when you're not using them.
FORGET ABOUT INFRASTRUCTURE
Deploying machine learning models at scale is hard. If you've tried, you know.
API servers, weird dependencies, enormous model weights, CUDA, GPUs, batching.
015305406:58 UTC07:22 UTC07:46 UTC08:10 UTC08:34 UTC08:58 UTC
Prediction throughput (requests per second)
LOGGING & MONITORING
Metrics let you keep an eye on how your models are performing, and logs let you
zoom in on particular predictions to debug how your model is behaving.
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IMAGINE WHAT YOU CAN BUILD
Autonomous Robots Zero-shot autonomous robots with open source models
Paint with AI An iPad app that lets you paint with AI
emojis.sh AI Emojis
Replicover Find the hottest AI models on Replicate
Language Model CLI Language model command line interface
Imagine
Autonomous Robots Zero-shot autonomous robots with open source models
what
you
Paint with AI An iPad app that lets you paint with AI
can
emojis.sh AI Emojis
Replicover Find the hottest AI models on Replicate
build.
Language Model CLI Language model command line interface
With Replicate and tools like Next.js and Vercel, you can wake up with an idea
and watch it hit the front page of Hacker News by the time you go to bed.
Get started
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Machine learning doesn’t need to be so hard.
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