PROMPT ENGINEERING

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Microsoft PromptFlow: Build Production-Ready LLM Applications

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@miketamir

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20 October 2023 17h37

microsoft/promptflow: Build high-quality LLM apps – from prototyping, testing to production deployment and monitoring. https://
bit.ly/46iENqu #AI #MachineLearning #DeepLearning #LLMs #DataScience

→ View original post on X — @cohere

Building Chatbots with Chat RAG and Memory

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@cohere

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20 October 2023 17h15

We’re excited to host our next Maker Spotlight live demo session today! Join Cohere community champions Arjun Patel and @Coffee_and_NLP in conversation with AI engineer @an1z8 as he walks us through leveraging Chat + RAG to build chatbot applications with memory and context.

Zero-shot Chain of Thought and Prompt Engineering Techniques

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20 October 2023 14h14

Some other prominent techniques include zero-shot chain of thought (beneficial for math or logic-related queries) and taking a step-by-step approach. Do not forget that a lot of this involves trial and error, continued practice, and patience.

Optimize LLMs: Test Models, Prompts, and Parameters Strategically

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20 October 2023 14h14

Maximize LLMs by actively trying different models, prompts, and parameters. Don't worry if it's daunting. Over time, you'll discern which tasks best match each LLM and its optimal settings.

Prompt Engineering Strategies to Boost LLM Performance

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20 October 2023 14h14

Prompt engineering enhances LLM efficiency, adjusting creativity, simplicity, and role clarity. However, strategies effective for one model may not suit another. Few-shot and chain-of-density prompting can boost LLM performance (learn more in the video).

→ View original post on X — @jeremyphoward

Creative experimentation with DALL-E 3 image generation

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@jeremyphoward

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20 October 2023 7h11

My wife wanted me to show her Dall-e 3, and for some reason this was the first thing that jumped into my head

Retrieval Augmented Generation: Improving Model Accuracy and Safety

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19 October 2023 15h37

Lastly, if you're still experiencing issues related to answer accuracy, hallucinations or outdated documentation, consider using Retrieval Augmented Generations. These can make your model responses safer and more attuned to your needs.