3/3
Here are the papers for reference: Llama 2: Open Foundation and Fine-Tuned Chat Models: https://
arxiv.org/abs/2307.09288 DeBERTa: Decoding-enhanced BERT with Disentangled Attention: https://
arxiv.org/abs/2006.03654
LLMS
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Reference Papers for Llama 2 and DeBERTa Models
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DeBERTa-1.5B Outperforms Llama 2 on BoolQ Classification Task
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Interestingly, DeBERTa-1.5B (and encoder-only model) beats Llama 2 on BoolQ, which is a nice example that encoders still outperform large decoders on classification task. For fairness: The DeBERTa-1.5B model was likely finetuned on the training data 1/3
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Master Generative AI Fundamentals and LLM Skills Today
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#LLMs are all the rage so it’s important to level up your #generativeAI skills. Our Generative #AI Fundamentals on-demand training will teach you how to harness this new transformative technology successfully https://
bit.ly/43VlaTM -
Turn ChatGPT into Alex Hormozi for Free $100k Advice
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I turned ChatGPT into Alex Hormozi. It's like receiving $100,000 advice for free. Follow this thread for step by step tutorial on this powerful prompt:
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Specialize in AI Niches: Computer Vision, NLP, and Robotics
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6/ Specialize and Dive Deeper! AI is vast – choose your niche! Whether it's computer vision, natural language (#NLP) processing or #robotics, specialize to become an authority in your chosen field.
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ChatGPT evolved: 8 ways to use it
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People say chatGPT is dead. Not true. It's evolved. Here are 8 ways to use it:
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Skeleton of Thought: Post-processing for LLM hallucination reduction
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One of the more interesting AI papers I've come across: Skeleton of Thought (SoT) introduces a post-processing method (similar to Chain-of-Thought) to enhance the final response/output of an LLM. Future LLMs might adopt strategies like SoT to reduce hallucinations, increase
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Expression Language Composability Over Callbacks in Components
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because the expression language is more composable, callbacks may not be necessary as it may be easier just to run each component as its own for example, in the example above i took a stab at it and got: https://
gist.github.com/hwchase17/f93f
3043a5c9fe2b69e19e2674f80d19
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LLaMA2 Responsible Usage Guide Released by Meta
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LLaMA2 responsible usage guide(PDF): https://
scontent.fnbo1-1.fna.fbcdn.net/v/t39.8562-6/3
65271716_1020127512503290_6433760642443597145_n.pdf
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LLaMA2 Guide: Best Practices for LLM Development
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LLaMA2 came with this well-curated guide that includes best practices and resources for working with large language models, LLaMA in particular. This guide is a relevant resource for practitioners and developers(or basically anyone building with LLMs) as it covers important