PulseAugur
EN
LIVE 15:02:25

Qwen 3.5 agent training methods debated on Reddit

A user on Reddit is seeking advice on training a Qwen 3.5 model for multi-tool agent use. They are asking for guidance on whether to use supervised fine-tuning (SFT) followed by reinforcement learning (RL), or an RL-only approach. The user also inquired about effective reward function design for tool-use agents and strategies for handling parallel tool execution, specifically when a tool's output necessitates multiple subsequent tool calls. AI

IMPACT Discusses training methodologies for multi-tool agents, relevant for developers building specialized AI applications.

RANK_REASON User-generated discussion about training methods for a specific model.

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Qwen 3.5 agent training methods debated on Reddit

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/siri_1110 ·

    Training a Qwen 3.5 4B/9B agent for multi-tool use: SFT first or go directly to RL?

    <!-- SC_OFF --><div class="md"><p>To train Qwen 3.5 4B or 9B for a custom multi-tool agent workflow and would appreciate guidance from people who have done this successfully.</p> <p>A few questions:</p> <ol> <li><p>SFT → RL or RL-only?</p> <p>- Is it still recommended to first do…