Long Context
원문: long-context
Extend context windows of transformer models using RoPE, YaRN, ALiBi, and position interpolation techniques. Use when processing long documents (32k-128k+ tokens), extending pre-trained models beyond original context limits, or implementing efficient positional encodings. Covers
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Long Context: Extending Transformer Context Windows When to Use This Skill Use Long Context techniques when you need to: Process long documents (32k, 64k, 128k+ tokens) with transformer models Extend context windows of pre trained models (LLaMA, Mistral, etc.) Implement efficient positional encodings (RoPE, ALiBi) Train models with length extrapolation capabilities Deploy models that handle variable length inputs efficiently Fine tune existing models for longer contexts with minimal compute Key Techniques : RoPE (Rotary Position Embeddings), YaRN, ALiBi (Attention with Linear Biases), Position Interpolation Papers : RoFormer (arXiv 2104.09864), YaRN (arXiv 2309.00071), ALiBi (arXiv 2108.1240…
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