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Search Model Tuning , found 5 results

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Deepgram Cost Tuning

deepgram-cost-tuning

jeremylongshore/claude-code-plugins-plus-skills

Guides teams to cut Deepgram transcription costs by enforcing budget-aware requests, trimming audio duration, tracking usage, sending tiered alerts, and selecting the most cost-effective models based on quality needs.

TRL Reinforcement Fine-Tuning

fine-tuning-with-trl

Orchestra-Research/AI-Research-SKILLs

Provides TRL-based RLHF fine-tuning flows covering SFT, reward-model training, PPO, DPO, and GRPO so teams can align HuggingFace models with preferences using both pipeline scripts and CLI helpers.

Groq Performance Tuning

groq-performance-tuning

jeremylongshore/claude-code-plugins-plus-skills

Guides developers to optimize Groq API calls through model selection, streaming, semantic caching, and parallel orchestration so latency-sensitive applications get consistent sub-100ms inference.

LangChain Cost Tuning

langchain-cost-tuning

jeremylongshore/claude-code-plugins-plus-skills

Guides production LangChain deployments through token tracking, prompt trimming, model tiering, caching, and budget callbacks so you can monitor costs, optimize token usage, and stop overspending on LLM APIs.

LangChain Performance Tuning

langchain-performance-tuning

jeremylongshore/claude-code-plugins-plus-skills

Step-by-step guidance for benchmarking LangChain apps, enabling caching, batching, streaming, and prompt/model tuning to cut latency, boost throughput, and improve resource use when a pipeline feels slow.

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