was <100 examples, and i actually didnt even have a topic for each tweet…. it seems to work fine without topics (which I was a bit surprised by), if it hadnt i probably would have generated them with AI
PROMPT ENGINEERING
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Streamlit Twitter Clone App with LangChain Fine-tuning Exploration
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Streamlit app so you can play around with yourself here: https://
elon-twitter-clone.streamlit.app Code: https://
github.com/langchain-ai/t
witter-finetune
… Going to be exploring this in a webinar next week with @GregKamradt
, register here: -
Fine-tuning Models for Custom Tone: Elon Musk Example
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One of my favorite use cases for fine-tuning is getting a model to speak in a custom tone This is kinda hard to achieve with just prompting/few-shot Here's an example of fine-tuning a model to tweet like Elon Musk (compare it to what you get by just prompting)
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RAG Technique: Solving Modern LLM Limitations Without Fine-Tuning
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Let’s dive in to one of the most-talked about AI techniques—retrieval augmented generation (RAG)— that developers are using as a precursor to fine-tuning. It helps solve the recent issue of modern LLMs while being not-really-that-hard to implement.
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RAG: Retrieval Augmented Generation Explained for Enterprises
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RAG stands for retrieval augmented generation, which enables companies to fetch important data relative to a query in a prompt in order to improve its results.
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RAG Emerges as Developer Priority for Model Performance Optimization
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Among all the developers, experts, and sources I talk to, no subject comes up more than RAG. Developers are increasingly working with it as a precursor to fine-tuning to squeeze more performance out of less-powerful models.
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Implementing AI: accessibility and RLHF resources
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Still a great list. Today I would add to dive as soon as possible in implementing something yourself since recent AI developments have become so accessible. We still need more good book/ressources on RLHF, maybe @natolambert or @_lewtun will fill this gap soon 🙂
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ChatGPT Ultimate Prompting Guide: Essential Elements
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Here's the ChatGPT Ultimate Prompting Guide Important elements to include: 1. Tone
2. Format
3. Objective
4. Context
5. Examples If you don't get the right output, try again you will get it soon… It is because of the prompt, not the tech! #Genai #tech #skillsofthefuture -
LIMA dataset recommendation for instruction finetuning with high-quality examples
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Agreed! And there’s LIMA if you are looking for 1k high-quality examples for instruction finetuning:
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RAG Systems Evaluation: Noah Chatbot Lessons Learned
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We had a REALLY fun webinar on evaluating RAG systems yesterday For me, the highlight was Pedro from Tavrn talking about lessons learned when building Noah (their context-aware chatbot) Now on YouTube for some Friday afternoon viewing! https://
youtube.com/watch?v=fWC4Vx
olWAk
…