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✨ Finishing touches🧪 Generate unit tests (beta)
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zhewenl
commented
Feb 11, 2026
| # Note: thinker_max_new_tokens controls the thinker's generation limit (default 1024), | ||
| # which is separate from max_new_tokens. Cap it to avoid long waits. | ||
| result = full_model.generate( | ||
| **calib_batch, max_new_tokens=100, thinker_max_new_tokens=100 |
| result = full_model.generate(**calib_batch, max_new_tokens=100) | ||
| print("[DEBUG] pre_quantize: starting qwen3omni preview generation (max_new_tokens=100)...", flush=True) | ||
| result = full_model.generate( | ||
| **calib_batch, max_new_tokens=100, thinker_max_new_tokens=100 |
| # For Qwen3-Omni Thinking models, the thinker's token limit is controlled by | ||
| # a separate `thinker_max_new_tokens` param (default 1024), not `max_new_tokens`. | ||
| # Cap it to avoid unbounded chain-of-thought generation during calibration. | ||
| if "qwen3omni" in model.__class__.__name__.lower(): |
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Qwen3-Omni Thinking models have a separate
thinker_max_new_tokensparameter (default value =1024) that is independent of max_new_tokens.During calibration, setting max_new_tokens=1 only limits the talker — the thinker still generates up to 1024 tokens per sample, causing a ~500x slowdown that makes calibration extremely slow