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 rotary embeddings, attention biases, interpolation methods, and extrapolation strategies for LLMs.
Install
npx skills add davila7/claude-code-templates@long-contextRuns in your terminal. Adds the skill globally for Claude Code, Cursor, Codex and others; add -g -y to skip prompts.
What it does
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…
Excerpt from the skill's own SKILL.md. Read the full file on GitHub before installing: skills run with your agent's permissions.
View source on GitHubBefore you install
Skills are plain text instructions the agent follows, sometimes with scripts. Check the source, prefer repositories with many installs and stars, and read any script it ships.
Categories
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