{
  "changeLog": "",
  "cpu": 0,
  "description": "This is the preview version of a generic, retrainable model for English Classification. This ML Package must be retrained, if deployed without training first, deployment will fail with an error stating that the model is not trained. This model is a deep learning architecture for language classification. It is based on RoBERTa, a self-supervised method for pretraining natural language processing systems. A GPU can be used both at serving time and training time. A GPU delivers ~5-10x improvement in speed. The original paper can be found here https://arxiv.org/abs/1907.11692 by Yinhan Liu, Myle Ott et al. The model was open-sourced by Facebook AI Research.",
  "displayName": "EnglishTextClassification",
  "gpu": 0,
  "inputDescription": "Text to be classified as String: 'I loved this movie.'",
  "inputType": "JSON",
  "memory": 0,
  "mlPackageLanguage": "PYTHON36",
  "name": "EnglishTextClassification",
  "outputDescription": "JSON with pedicted class name, associated confidence on that class prediction (between 0-1).  For example: {\"prediction\": \"Positive\", \"confidence\": 0.9422031841278076,}",
  "processorType": "GPU",
  "retrainable": true,
  "stagingUri": "[staging-uri]",
  "projectId": "[project-id]",
  "projectName": "Language Analysis",
  "projectDescription": "Models for analyzing text including language detection, sentiment analysis, and named-entity recognition.",
  "tenantName": "Open-Source Packages",
  "minAIFabricVersion": "v21.10",
  "languageVersion": 0,
  "version": 2,
  "contentUri": "https://<placeholder-url>/publicmodels/AIC/EnglishTextClassification/2/EnglishTextClassificationAG.zip"
}