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Search Tuning , found 64 results

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Axolotl LLM Fine-Tuning

Orchestra-Research/AI-Research-SKILLs

Expert guidance for fine-tuning LLMs with Axolotl, covering YAML configs, LoRA/QLoRA/DPO variants, multimodal support, and practical troubleshooting patterns for development and training workflows.

Axolotl LLM Fine-Tuning

Orchestra-Research/AI-Research-SKILLs

Expert guidance for fine-tuning LLMs with Axolotl, covering YAML configs, LoRA/QLoRA/DPO variants, multimodal support, and practical troubleshooting patterns for development and training workflows.

Blip2 Vision Language

blip-2-vision-language

Orchestra-Research/AI-Research-SKILLs

Bridges frozen vision encoders and LLMs for high-quality image captioning, VQA, retrieval, and multimodal chat, enabling zero-shot reasoning without fine-tuning and offering efficient Q-Former training.

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.

CLIP Vision-Language Toolkit

Orchestra-Research/AI-Research-SKILLs

CLIP enables general-purpose vision-language tasks through zero-shot image classification, similarity scoring, semantic search, and content moderation using pretrained contrastive embeddings without fine-tuning.

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.

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.

LLM Fine-Tuning Guide

fine-tuning-expert

Jeffallan/claude-skills

Guides ML engineers through dataset prep, PEFT strategy selection, LoRA/QLoRA adapter setup, training monitoring, and deployment checks for practical LLM fine-tuning, quantization, and adapter merge workflows.

TRL RLHF Pipeline

fine-tuning-with-trl

Orchestra-Research/AI-Research-SKILLs

Fine-tune LLMs with TRL’s RLHF toolkit, covering SFT, DPO, PPO/GRPO and reward model training so you can align HuggingFace Transformers with human preferences or feedback in post-training workflows.

GRPO RL Fine-Tuning

grpo-rl-training

Orchestra-Research/AI-Research-SKILLs

Provides expert guidance for GRPO training with TRL, covering dataset prep, reward engineering, structured outputs, and multi-objective alignment when preference pairs are scarce.

Half-Quadratic Quantization

hqq-quantization

Orchestra-Research/AI-Research-SKILLs

Provides calibration-free weight quantization for LLMs down to 1-bit precision with multiple optimized backends, ideal for fast deployments with vLLM/HuggingFace and LoRA/PEFT fine-tuning without collecting calibration data.

Hyperparameter Tuner Assistant

hyperparameter-tuner

jeremylongshore/claude-code-plugins-plus-skills

Automated guidance for hyperparameter tuning within ML training workflows, offering best practices, production-ready code, and validation across modeling stages like data prep, training, and experiment tracking.

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