Welcome to the FAQ page for Infermatic.ai! Here, you can find answers to your questions about large language models and the AI industry. Whether you’re curious about how to use our tools or want to learn more about AI, this page is a great place to start.
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- What are the key differences between traditional machine learning and deep learning approaches to natural language processing?
- How does Infermatic.ai's use of transformer-based architectures improve the accuracy of sentiment analysis tasks?
- Can you explain the role of pre-training and fine-tuning in the context of large language models like those used by Infermatic.ai?
- What are some common challenges in text classification tasks, and how do large language models like Infermatic.ai address them?
- How does Infermatic.ai's approach to natural language processing handle out-of-vocabulary words or unseen entities?
- What is the significance of attention mechanisms in large language models, and how does it impact text classification and sentiment analysis?
- Can you describe the role of contextualized embeddings in improving the performance of natural language processing tasks, such as sentiment analysis and text classification?
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