Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds....
AI & LLM
LLM integrations, prompt engineering, and AI orchestration
7,400 skills
Language-independent tokenizer treating text as raw Unicode. Supports BPE and Unigram algorithms. Fast (50k...
Expert guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training
Provides guidance for enterprise-grade RL training using miles, a production-ready fork of slime. Use when training...
High-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models...
Simple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4...
Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM...
Provides guidance for PyTorch-native agentic RL using torchforge, Meta's library separating infra from algorithms....
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...