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Qwen3: LLM Steerable Recommendations
Learn how to fine‑tune Qwen3‑8B to embed product IDs in its vocabulary, generate recommendations from interaction data, and steer results via conversational prompts.
I’ll be demoing how I finetuned Qwen3-8B to understand product IDs. The result is a language model that can converse in both English and item IDs, not with retrieval or other tools, but as a single, “bilingual” model where items (i.e., semantic IDs) are part of its vocabulary. Like a recommender model, it can recommend items given historical interactions. But the big surprise—and capability unlock—was when I found that I could simply chat with the model to steer its recommendations, and it could reason about its choices, offer explanations, and creatively name product bundles.
RQ-VAE generated Semantic IDs train Qwen3-8B for conversational, steerable recommendation generation.
Qwen3-8B finetuning incorporates RQ-VAE Semantic IDs for unified LLM recommenders.