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slime

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Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL scaling.

When to use

• Megatron-LM native training with SGLang inference
• Custom data generation workflows with flexible data buffers
• Training GLM, Qwen3, DeepSeek V3, or Llama 3 models
• Research-grade framework with production backing (Z.ai)
• You need enterprise-grade stability features → use **miles**
• You want flexible backend swapping → use **verl**
• You need PyTorch-native abstractions → use **torchforge**

When not to use

• enterprise-grade stability features
• flexible backend swapping
• PyTorch-native abstractions

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