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Search Model Tuning , found 31 results

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Transfer Learning Adaptation Skill

adapting-transfer-learning-models

jeremylongshore/claude-code-plugins-plus-skills

Automates adapting pretrained models via transfer learning by analyzing requirements, generating PyTorch or TensorFlow fine-tuning code, validating data, tracking KPIs, and saving artifacts so you can quickly reuse existing models for new datasets and tasks.

Classification Model Builder

building-classification-models

jeremylongshore/claude-code-plugins-plus-skills

Automates building and evaluating classification models by analyzing datasets, selecting features, tuning hyperparameters, and reporting metrics via the classification-model-builder plugin for supervised learning requests.

Neural Network Builder

building-neural-networks

jeremylongshore/claude-code-plugins-plus-skills

Enables Claude to configure neural network architectures through the neural-network-builder plugin, creating or modifying models and defining layers, activation functions, and training parameters whenever network design or tuning is requested.

AutoML Pipeline Builder

building-automl-pipelines

jeremylongshore/claude-code-plugins-plus-skills

Builds AutoML pipelines by analyzing user requests, generating code for data preparation, model selection, hyperparameter tuning, validation, and metrics, then documenting artifacts for streamlined automated machine learning workflows.

Cross Validation Setup

cross-validation-setup

jeremylongshore/claude-code-plugins-plus-skills

Automates cross validation setup for ML training requests, offering best-practice guidance, production-ready code samples, and validation steps across data preparation, model tuning, and experiment tracking.

Dataset Loader Creator

dataset-loader-creator

jeremylongshore/claude-code-plugins-plus-skills

Automates dataset loader creation within ML Training workflows, offering best-practice guidance, validation checks, and production-ready code to accelerate data prep and model tuning.

Deepgram Cost Tuning

deepgram-cost-tuning

jeremylongshore/claude-code-plugins-plus-skills

Optimize Deepgram transcription costs by picking the right models, preprocessing audio, caching results, and enforcing usage budgets for predictable, budget-conscious deployments.

Feature Engineering Helper

feature-engineering-helper

jeremylongshore/claude-code-plugins-plus-skills

Automatically activates when you mention feature engineering helper, offering guidance on data preparation, model training, hyperparameter tuning, and experiment tracking for ML projects.

Feature Importance Analyzer

feature-importance-analyzer

jeremylongshore/claude-code-plugins-plus-skills

Automates guidance on assessing feature importance for machine learning training, covering data prep, model training, tuning, and experiment tracking while generating production-ready code, configurations, and validation instructions for best-practice compliance.

Fine-Tuning LLM Expert

fine-tuning-expert

Jeffallan/claude-skills

Hands-on guide for tuning large language models via LoRA/QLoRA/PEFT, covering dataset prep, hyperparameter config, adapter training, evaluation, and production deployment with quantization best practices.

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.

Half Quadratic Quantization

hqq-quantization

Orchestra-Research/AI-Research-SKILLs

Calibrate-free half-quadratic quantization for LLMs that delivers 1-8 bit model compression with configurable backends (PyTorch, TorchAO, BitBlas, Marlin). Ideal for fast quantization workflows, zero-data deployment, and PEFT/LoRA fine-tuning with HuggingFace or vLLM stacks.

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