字節祭出開源祕密武器HybridFlow，大模型訓練速度飆升20倍，成本砍到腳脖子！
大模型（LLM）如GPT、Llama等在人工智能領域掀起了一場革命，但如何高效地訓練這些龐大的模型並使其符合人類價值觀仍然是一個難題。強化學習與人類反饋（RLHF）作爲一種重要的LLM訓練方法，近年來得到廣泛應用，但傳統的RLHF框架在靈活性、效率和可擴展性方面存在侷限性。爲解決這些問題，字節跳動豆包大模型團隊開源了名爲HybridFlow的RLHF框架，爲LLM訓練帶來了新的可能性。RLHF通常包含三個階段:首先，actor模型根據輸入的提示生成文本;然後，critic模型、reference模型和reward模型對生成
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