minimind

Author	SHA1	Message	Date
baihaochen	bc3d137248	[feat] add MLA with decoupled RoPE (DeepSeek-V2 style) - Add model_minimind_mla.py with Q/KV low-rank compression and decoupled RoPE - Add kv_norm on kv_latent, q_compress + q_up + q_rope_proj for Q path - Cache format: (kv_latent, k_rope) tuple, 176 floats/tok/layer (4.4x compression) - Add --use_mla flag to all training scripts and utils - Add benchmark_gqa_vs_mla.py script	2026-05-12 18:38:47 +08:00
jingyaogong	b1865f75c2	[update] random seed	2026-03-27 21:20:02 +08:00
jingyaogong	6b0b0c5e2f	[update] fp16 inference	2026-03-27 16:29:46 +08:00
jingyaogong	101d7df2da	[update] minimind-3	2026-03-25 23:57:45 +08:00
jingyaogong	05d0b216f6	[update] show speed	2026-01-07 23:33:47 +08:00
jingyaogong	288a1d7212	[feat] get params	2025-12-31 20:44:34 +08:00
jingyaogong	08ce3da228	[feat] update args	2025-10-30 10:48:31 +08:00
jingyaogong	bf123b585d	[feat] add args	2025-10-30 10:05:12 +08:00
jingyaogong	35bed8936d	[feat] update eval-llm	2025-10-26 18:52:01 +08:00
jingyaogong	4e35fb9da8	[fix] update model	2025-10-17 00:09:32 +08:00
jingyaogong	36159fb2ab	update app	2025-10-16 23:33:35 +08:00