In the rapidly evolving landscape of AI and machine learning, accessing powerful language models has become easier than ever. With advancements like the llama_cpp Python library and the wealth of models available on platforms like Hugging Face, running sophisticated language models on your local machine is now within reach. In this article, we’ll explore how to unleash the capabilities of a small language model called Phi2 using just 15 lines of Python code.
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In the realm of data analysis and manipulation, SQL (Structured Query Language) stands as a cornerstone for interacting with relational databases. However, crafting SQL queries can sometimes be daunting, especially for those less familiar with the language. Enter SQLCoder2-7B, a cutting-edge model that leverages the power of natural language processing (NLP) to generate SQL queries from plain text. In this guide, we’ll explore how to utilize SQLCoder2-7B with the Yelp dataset, diving into the implementation details using llama_cpp and a compatible gguf model from Hugging Face.
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In the ever-evolving landscape of artificial intelligence (AI) and machine learning, the demand for diverse and expansive datasets has become paramount. Real-world data, while invaluable, often presents challenges such as privacy concerns, limited access, and scalability issues. This is where the concept of synthetic data comes into play, offering an innovative solution to these challenges.
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