I am passionate about new technologies and have a strong focus and experience in the areas of Machine Learning and Deep Learning, particularly in Natural Language Processing.
Nothing here yet.
Azure OCR considers many factors in order to recognize text with high accuracy, such as the font size, style, noise, and orientation of the text in an image. You can try using different images and see if the text ordering is the same or different. Unfortunately, I cannot provide a Jupyter notebook with code as this task is confidential. However, I have provided all the information you might need in the blog. Please let me know if you still require assistance. You can find me here: https://rupeshgelal.com.np/.
In this case, yes, I have fine-tuned the model for a specific schema. You can try using your own schema. As for your second question, I'm not sure I understand it fully. If you're asking how the model predicts which fields to use based on the prompt, it has an overall understanding of the schema, including the tables and their columns. I prepared the training dataset in a way that includes all the information about our schema, which gives the model a better understanding of our task