Skills with input "training dataset"

verl-rl-training - RL Training Library for LLMs
Reinforcement Learning RLHF GRPO PPO
★ 602 · Updated 2026-06-30
Provides guidance for training LLMs with RL using verl library
⚙ train models with RLHF ⚙ train models with GRPO ⚙ train models with PPO
verl-rl-training - LLM Reinforcement Learning Training with Verl
Reinforcement Learning RLHF Post-Training Distributed Training
★ 0 · Updated 2026-06-30
Train LLMs at scale using verl with PPO, GRPO, and other RL algorithms
⚙ train models with PPO ⚙ train models with GRPO ⚙ configure RL algorithms
verl-rl-training - Train LLMs with verl RL library
Reinforcement Learning RLHF Model Training Distributed Computing
★ 1 · Updated 2026-06-30
Flexible RL training library for large language models supporting multiple algorithms and backends
⚙ train LLM with GRPO algorithm ⚙ train LLM with PPO algorithm ⚙ train LLM with RLOO algorithm
verl-rl-training - RL Training for LLMs with verl
LLM Reinforcement Learning Training Distributed Systems
★ 0 · Updated 2026-06-30
Train large language models with reinforcement learning algorithms using the verl library
⚙ implement RLHF ⚙ configure GRPO ⚙ run PPO
knowledge-distillation-deep - Compress Large Models via Knowledge Distillation
knowledge-distillation model-compression deep-learning transfer-learning
★ 11 · Updated 2026-06-30
Deep analysis of techniques for compressing large models into smaller efficient ones via distillation
⚙ select distillation strategy ⚙ configure temperature parameters ⚙ set alpha values
pytorch-guide - PyTorch Training Best Practices Guide
PyTorch deep learning model training GPU
★ 3,789 · Updated 2026-06-15
Catalog common PyTorch mistakes and provide battle-tested training patterns and optimization techniques
⚙ detect common PyTorch mistakes ⚙ provide training templates ⚙ fix evaluation mode issues
pytorch-lightning - PyTorch Lightning Training Framework
Training Framework Distributed Training PyTorch Lightning Deep Learning
★ 3 · Updated 2026-05-28
High-level PyTorch framework with automatic distributed training and minimal boilerplate
⚙ train model ⚙ validate model ⚙ test model
slipstream-finetune - Finetune LLMs for Slipstream Protocol
LLM finetuning Slipstream protocol GLM-4 dataset generation
★ 602 · Updated 2026-03-26
Train LLMs to communicate natively using the Slipstream protocol
⚙ generate dataset ⚙ finetune model ⚙ test model
unsloth-finetuning - Fine-tune LLMs with Unsloth
LLM fine-tuning 4-bit quantization LoRA
★ 602 · Updated 2026-03-26
Fine-tune LLMs with Unsloth using 4-bit quantization and LoRA
⚙ load 4-bit quantized models ⚙ configure LoRA parameters ⚙ train on datasets
Model Bias Fairness - AI Model Bias Detection and Fairness
api backend server database
★ 602 · Updated 2026-03-22
Detect systematic bias in AI systems and ensure predictions do not vary unfairly across protected attributes
⚙ detect model bias ⚙ verify fairness metrics ⚙ analyze model predictions
PyTorch ML - PyTorch Deep Learning Environment
deep learning machine learning GPU acceleration computer vision
★ 15 · Updated 2026-03-21
Complete machine learning environment with PyTorch for model training and GPU acceleration
⚙ define neural network ⚙ load pretrained model ⚙ train model
distributed-training - Distributed Training Parallelism Strategies
machine learning distributed training GPU parallel deep learning
★ 2 · Updated 2026-03-10
Provides guidance for scaling ML training across multiple GPUs and nodes with parallelism strategies
⚙ train across multiple GPUs ⚙ select parallelism strategy ⚙ synchronize gradients