Capsa quantifies model uncertainty and de-risks outputs, enabling AI quality assurance and compliance.

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import torch

import capsa_torch

_model = Model()*# Wrap your model*model = capsa_torch.wrapper(_model)*# Your model is now uncertainty-aware*pred, risk = model(input, return_risk=True)

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import tensorflow as tf

import capsa_tf*# Add a decorator*

@capsa_tf.Wrapper()

@tf.function

def model(...):

...*# Your model is now uncertainty-aware*pred, risk = model(input, return_risk=True)

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Capsa, our proprietary technology, is built to be compatible with any ML model, seamlessly working in a matter of seconds at any stage of development.

Capsa enables users to detect and correct unreliable outputs produced by ML models, ensuring consistent high-quality results.

import torch import capsa_torch _model = Model () model = capsa_torch.wrapper (_model) pred, risk = model (input, return_risk=True) import tensorflow as tf import capsa_tf @capsa_tf.Wrapper () @tf. function def model (...): pred, risk = model (input, return_risk=True)

import tensorflow as tf import capsa_tf @capsa_tf.Wrapper () @tf. function def model (...): pred, risk = model (input, return_risk=True) import torch import capsa_torch _model = Model () model = capsa_torch.wrapper (_model) pred, risk = model (input, return_risk=True)