joehoover / bart-large-mnli

Zero-shot classification document classification with a light-weight model.

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  • 56 runs
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Run joehoover/bart-large-mnli with an API

Use one of our client libraries to get started quickly. Clicking on a library will take you to the Playground tab where you can tweak different inputs, see the results, and copy the corresponding code to use in your own project.

Input schema

The fields you can use to run this model with an API. If you don't give a value for a field its default value will be used.

Field Type Default value Description
input
string
Replicate, I think I might...like you a lot!
Text sequence to classify.
class_labels
string
positive, negative, neutral
Class names. Must be a comma-delimited string of labels.
multi_label
boolean
False
If True, then class scores are independent.
hypothesis_template
string
This example is {}.
Hypothesis into which class labels are piped. Must contain '{}'.

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema
{
  "type": "object",
  "title": "Output"
}