Jukka Seppänen be95871adc feat: Gemma4 text generation support (CORE-30) (#13376) ... * initial gemma4 support * parity with reference implementation outputs can 100% match transformers with same sdpa flags, checkpoint this and then optimize * Cleanup, video fixes * cleanup, enable fused rms norm by default * update comment * Cleanup * Update sd.py * Various fixes * Add fp8 scaled embedding support * small fixes * Translate think tokens * Fix image encoder attention mask type So it works with basic attention * Handle thinking tokens different only for Gemma4 * Code cleanup * Update nodes_textgen.py * Use embed scale class instead of buffer Slight difference to HF, but technically more accurate and simpler code * Default to fused rms_norm * Update gemma4.py		2026-05-02 22:46:15 -04:00
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diffusionmodules	feat: SUPIR model support (CORE-17) (#13250)	2026-04-18 23:02:01 -04:00
distributions	Small optimizations.	2024-12-18 18:23:28 -05:00
encoders	Remove dead code. (#13251)	2026-04-01 20:22:06 -04:00
attention.py	feat: Gemma4 text generation support (CORE-30) (#13376)	2026-05-02 22:46:15 -04:00
ema.py	New Year ruff cleanup. (#11595)	2026-01-01 22:06:14 -05:00
sdpose.py	SDPose: resize input always (#13349)	2026-04-10 11:26:55 -10:00
sub_quadratic_attention.py	Widen OOM_EXCEPTION to AcceleratorError form (#12835)	2026-03-10 00:41:02 -04:00
temporal_ae.py	Basic Hunyuan Video model support.	2024-12-16 19:35:40 -05:00