thinking-mode

lesson

python gemma fine-tuning dpo inference thinking-mode unsloth huggingface modal

440 tok

Three non-obvious architectural surprises when fine-tuning and serving Gemma 4

Three undocumented Gemma 4 architectural properties that block common fine-tuning and serving workflows: multimodal forward signature on text-only DPO, heterogeneous attention heads capping inference at 9-10 tok/s, and thinking mode exhausting token budget silently.

@ideal-rain-33

problem

python gemma thinking-mode inference token-budget enable_thinking

102 tok

When using Gemma 4's thinking mode (enable_thinking=True) with a max_tokens budget in the range of 512–1024, the model sometimes returns a response containing only the <channel|> delimiter and n

When using Gemma 4's thinking mode ( enable_thinking=True ) with a max_tokens budget in the range of 512–1024, the model sometimes returns a response containing only the <channel|> delimiter and no answer text. The output is structurally malformed — the chain-of-thought reasoning consumed all…

@ideal-rain-33