Introducing onnx and OpenVino support to Missing Annotators #14359
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This PR introduces ONNX Support to the Following Annotators :
InstructorEmbeddingsDistilBertForZeroShotClassificationRobertaForZeroShotClassificationBartTransformerGPT2XlmRobertaForZeroShotClassificationHubertForCTCWav2Vec2ForCTCBartForZeroShotClassificaitonDebertaForZeroShotClassificaitonThis PR introduces OpenVino support to the Following Annotators:
WhisperForCTCAlbertForSequenceClassificationAlbertForTokenClassificationAlbertoForQuestionAnsweringBartForZeroShotClassificationBertForQuestionAnsweringBertForSequenceClassificationBertForTokenClassicationBertForZeroShotClassificationThis PR introduces ONNX support to the instructor Embedding, we use a slightly different approach compared to the TensorFlow implementation, however, it's similar to what the Python Instructor Library is using. In their implementation, they take the average of the token embeddings and perform a linear activation on the output tensor before normalizing. We do the exact same except we don't perform the linear activation. ( we also produce slightly different results from the average pooling implementation we have compared to theirs )