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.

Install the Python library

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

pip install replicate

Authenticate

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/sdxl:

import replicate

output = replicate.run(
  "stability-ai/sdxl:39ed52f2a78e934b3ba6e2a89f5b1c712de7dfea535525255b1aa35c5565e08b",
  input={"prompt": "an iguana on the beach, pointillism"}
)

# ['https://replicate.delivery/pbxt/VJyWBjIYgqqCCBEhpkCqdevTgAJbl4fg62aO4o9A0x85CgNSA/out-0.png']

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 = "https://example.com/mystery.jpg"

replicate.run(
  "replicate/resnet:dd782a3d531b61af491d1026434392e8afb40bfb53b8af35f727e80661489767",
  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 = replicate.run(
  "mistralai/mixtral-8x7b-instruct-v0.1",
  input={"prompt": "Who was Dolly the sheep?"},
)
for text in iterator:
      print(text)

      🐑
      D
     olly
      the
      sheep
      was
      the
      first
      mamm
     al
      to
      be
      successfully
      cl
     oned
      from
      an
      adult
      cell
     ...

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.