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tomasvotruba.com | ||
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ollama.ai
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| | | | | This guide walks through the different ways to structure prompts for Code Llama and its different variations and features including instructions, code completion and fill-in-the-middle (FIM). | |
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isthisit.nz
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| | | | | August 2024 Update: Now a solved problem. Use Structured Outputs. Large language models (LLMs) return unstructured output. When we prompt them they respond with one large string. This is fine for applications such as ChatGPT, but in others where we want the LLM to return structured data such as lists or key value pairs, a parseable response is needed. In Building A ChatGPT-enhanced Python REPL I used a technique to prompt the LLM to return output in a text format I could parse. | |
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www.markhw.com
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| | | | | [AI summary] This blog post discusses integrating R and Python for seamless data analysis using OpenAI's GPT models to extract information from Wikipedia about film directors' roles in Oscar-winning films. | |
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thathelpfuldad.com
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| | | As artificial intelligence continues to evolve, Google Bard and OpenAI's ChatGPT have emerged as leading AI-powered tools for a variety of tasks. Both are designed to generate human-like text, but they have different strengths and capabilities. Here, we'll compare these two tools to help you understand which is best suited for specific tasks. Overview of... | ||
