Published on Medium, Towards Data Science, and ZAAI's Lab, this collection of articles ventures into the captivating areas of Natural Language Processing (NLP) and Large Language Models (LLMs). Here, we invite you to explore our AI passion as we share open-source code, datasets, and abundant resources. Our aim is to empower individuals and organizations, enabling them to track our experiments, find inspiration, and solve complex use cases in their own domains.
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Seeing with Sound: Empowering the Visually Impaired with GPT-4V(ision) and Text-to-Speech Technology
- Published on Nov 16, 2023, Co-authored Luís Roque and Rafael Guedes
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The Power of Retrieval Augmented Generation: A Comparison between Base and RAG LLMs with Llama2
- Published on Nov 29, 2023, Co-authored Luís Roque and Rafael Guedes
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Decoding LLMs: Creating Transformer Encoders and Multi-Head Attention Layers in Python from Scratch
- Published on Dec 1, 2023, Co-authored Luís Roque and Rafael Nardi
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Revolutionizing Language Barriers: Mastering Multilingual Audio Transcription and Semantic Search
- Published on Dec 13, 2023, Co-authored Luís Roque and Rafael Guedes
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- Published on Jan 4, 2024, Co-authored Luís Roque and Rafael Guedes
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LLMs and Transformers from Scratch: the Decoder
- Published on Jan 10, 2024, Co-authored Luís Roque and Rafael Nardi
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Mistral AI vs. Meta: Comparing Top Open-source LLMs
- Published on Jan 23, 2024, Co-authored Luís Roque and Rafael Guedes
Clone the repository using the following command:
git clone https://github.com/zaai-ai/large-language-models.git
Each article is contained within its own directory. All dependencies and instructions specific to those experiments are found within the respective directories and are self-contained.
This project is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License. This means you are free to adapt and distribute the contents of this repository for non-commercial purposes as long as you provide proper attribution.
For any commercial use, please request permission.
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