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Post-Training
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GPTQ LLM Quantization
gptq
Orchestra-Research/AI-Research-SKILLs
419
Post-training 4-bit quantization for LLMs that trims memory by 4× with minimal perplexity loss, enabling 70B+ models to run faster on consumer GPUs while integrating with transformers, PEFT, and QLoRA workflows.
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Slime RL Training
slime-rl-training
Orchestra-Research/AI-Research-SKILLs
214
Guides LLM post-training with reinforcement learning using the Slime (Megatron + SGLang) framework, covering GLM-style training, custom data buffers, rollout management, and Megatron-LM integration for scalable policy tuning.
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1
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简体中文
English