Llama
A comprehensive skill catalog for AI agents
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Meta Llama open-source LLM family. Use for local AI.
SKILL.md
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Llama
Meta Llama is the king of Open Weights models. Llama 4 (2025) pushes 405B+ parameters, rivaling closed models like GPT-5.
When to Use
- Privacy: Run it on your own VPC (AWS Bedrock, Azure, or self-hosted).
- Fine-Tuning: It is the default base model for fine-tuning on domain data.
- Cost: Inference on Groq/Together AI is significantly cheaper than GPT.
Core Concepts
Models
- 405B: Frontier intelligence. Requires massive GPU clusters (or API).
- 70B: The workhorse. Smart enough for most tasks.
- 8B: Runs on a laptop (MacBook M3).
Quantization
Running models at 4-bit or 8-bit precision to fit in VRAM with minimal quality loss (GGUF, EXL2).
Llama Stack
Standardized tooling for building agentic apps on Llama.
Best Practices (2025)
Do:
- Use via API: Groq (LPU) runs Llama Instantaneously (>1000 tok/s).
- Fine-Tune 8B: For specific tasks (classification, SQL generation), a fine-tuned 8B beats a generic 70B.
Don't:
- Don't self-host 405B: Unless you have 8xH100s. Use an API provider.