OpenAI logoCLIP

A classification model for matching a provided image a label from a provided set.

Deploy CLIP behind an API endpoint in seconds.

Deploy model

Example usage

This code example shows how to invoke the model using the requests library in Python. The model has one input:

url: The URL for any image

The output of the model is a list containing the probabilities of the image belonging to a certain class.

Input
1import requests
2import os
3
4# Replace the empty string with your model id below
5model_id = ""
6baseten_api_key = os.environ["BASETEN_API_KEY"]
7
8data = {
9    "url": "https://images.pexels.com/photos/1170986/pexels-photo-1170986.jpeg?auto=compress&cs=tinysrgb&w=1600"
10}
11
12# Call model endpoint
13res = requests.post(
14    f"https://model-{model_id}.api.baseten.co/production/predict",
15    headers={"Authorization": f"Api-Key {baseten_api_key}"},
16    json=data
17)
18
19# Print the output of the model
20print(res.json())
JSON output
1[
2    [
3        0.9919015765190125,
4        0.008098451420664787
5    ]
6]

Deploy any model in just a few commands

Avoid getting tangled in complex deployment processes. Deploy best-in-class open-source models and take advantage of optimized serving for your own models.

$

truss init -- example stable-diffusion-2-1-base ./my-sd-truss

$

cd ./my-sd-truss

$

export BASETEN_API_KEY=MdNmOCXc.YBtEZD0WFOYKso2A6NEQkRqTe

$

truss push

INFO

Serializing Stable Diffusion 2.1 truss.

INFO

Making contact with Baseten πŸ‘‹ πŸ‘½

INFO

πŸš€ Uploading model to Baseten πŸš€

Upload progress: 0% | | 0.00G/2.39G