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The KV Cache: Memory Usage in Transformers (Efficient NLP) View |
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Train Llama 2 from Scratch in PyTorch Locally (Fahd Mirza) View |
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Rotary Positional Embeddings: Combining Absolute and Relative (Efficient NLP) View |
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RoPE (Rotary positional embeddings) explained: The positional workhorse of modern LLMs (DeepLearning Hero) View |
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Variants of Multi-head attention: Multi-query (MQA) and Grouped-query attention (GQA) (Machine Learning Studio) View |
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Llama 2 Paper Explained (Rajistics - data science, AI, and machine learning) View |
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LLAMA 2 paper explained - first free commercial model vs ChatGPT! (AI Bites) View |
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Code Llama Paper Explained (AI Papers Academy) View |
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LLama 2: Andrej Karpathy, GPT-4 Mixture of Experts - AI Paper Explained (Harry Mapodile) View |
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Pytorch for Beginners #42 | Transformer Model: Implement Decoder (Makeesy AI) View |