Run a model from Python

Learn how to run a model on Replicate from within your Python code. It could be an app, a notebook, an evaluation script, or anywhere else you want to use machine learning.

👋 Check out an interactive version of this tutorial on Google Colab.

Open In Colab

Install the Python library

We maintain an open-source Python client for the API. Install it with pip:

pip install replicate


Authenticate by setting your token in an environment variable:

Run predictions

You can run any public model on Replicate from your Python code. The following example runs stability-ai/stable-diffusion:

import replicate
  input={"prompt": "a 19th century portrait of a wombat gentleman"}

# ['']

Some models, like replicate/resnet in the following example, receive images as inputs. To pass a file as an input, use a file handle or URL:

image = open("mystery.jpg", "rb")
# or...
image = ""
  input={"image": image}

URLs are more efficient if your file is already in the cloud somewhere, or it is a large file. Files are output as URLs.

Some models stream output as the model is running. They will return an iterator, and you can iterate over that output:

iterator =
  input={"prompts": ["robots talking to robots"]},
for image in iterator:

# https://...
# https://...
# https://...

Next steps

Read the full Python client documentation on GitHub.

You can also run models with the raw HTTP API. Refer to the HTTP API reference for more details.