1 个仓库
Awesome GitHub RepositoriesAsync Request Throughput Optimizers
Sending multiple concurrent requests to increase the rate of text generation or training throughput.
Distinct from Training Throughput Optimization: Distinct from Training Throughput Optimization: focuses on async request concurrency for inference and training, not batch size selection.
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Awesome Async Request Throughput Optimizers GitHub Repositories
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- thinking-machines-lab/tinker-cookbook
thinking-machines-lab/tinker-cookbook
2,856在 GitHub 上查看Tinker Cookbook is an open-source framework for fine-tuning large language models, supporting supervised learning, reinforcement learning, and parameter-efficient techniques like LoRA adapters. It provides a complete pipeline for aligning models with human preferences through multi-stage RLHF workflows, from supervised fine-tuning through preference optimization to reinforcement learning. The framework distinguishes itself through recipe-based training orchestration, where fine-tuning workflows are defined as composable recipe files that chain data loading, model configuration, and training l
Optimizes throughput by sending multiple concurrent generation requests asynchronously.
Python
