Provides guidance for PyTorch-native agentic RL using torchforge, Meta's library separating infra from algorithms....
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Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment,...
Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when...
Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO,...
Expert guidance for fine-tuning LLMs with LLaMA-Factory - WebUI no-code, 100+ models, 2/3/4/5/6/8-bit QLoRA,...
Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models...
Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization
Provides guidance for interpreting and manipulating neural network internals using nnsight with optional NDIF remote...
Provides guidance for performing causal interventions on PyTorch models using pyvene's declarative intervention...
Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network...
Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate...
GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16×...
Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images....
Anthropic's method for training harmless AI through self-improvement. Two-phase approach - supervised learning with...
Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual...
NVIDIA's runtime safety framework for LLM applications. Features jailbreak detection, input/output validation,...
Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for...
Expert guidance for distributed training with DeepSpeed - ZeRO optimization stages, pipeline parallelism,...
Trains large language models (2B-462B parameters) using NVIDIA Megatron-Core with advanced parallelism strategies....
Expert guidance for Fully Sharded Data Parallel training with PyTorch FSDP - parameter sharding, mixed precision,...
High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks...
Distributed training orchestration across clusters. Scales PyTorch/TensorFlow/HuggingFace from laptop to 1000s of...
Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances...
Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without...