Roboflow Docs

ViT

Run ViT classification models trained on Roboflow via the Serverless Cloud API

Use Vision Transformer (ViT) classification models trained on Roboflow through the Serverless Cloud API.

ViT API

1

Get your API Key

Create a Roboflow account, find your key on the Roboflow API settings page and make it available to your shell:

export ROBOFLOW_API_KEY="your-key-here"
2

Install the dependencies

This package calls the model:

pip install -U inference-sdk supervision
3

Run the model

Call your trained ViT classifier by its {workspace}/{model-slug} ID (see Versions, Trainings, and Models).

import os
import supervision as sv
from inference_sdk import InferenceHTTPClient

image = sv.load_image_from_url("https://media.roboflow.com/notebooks/examples/dog.jpeg")

client = InferenceHTTPClient(
    api_url="https://serverless.roboflow.com",
    api_key=os.environ["ROBOFLOW_API_KEY"],
)
# No pretrained aliases: train your own model and replace "your-project/1" with your model ID.
results = client.infer(image, model_id="your-project/1")
print(results)

Set api_url to match your deployment target:

  • https://serverless.roboflow.com for the Serverless Cloud API.
  • http://localhost:9001 for a local Inference server.
  • Your Dedicated Deployment URL for a private endpoint.

For self-hosted deployment and additional details, see the Inference documentation.