model : add support for MiniMaxText01ForCausalLM and MiniMaxM1ForCausalLM (#27018)

* llama : support for MiniMax-Text-01 model

* chore : renames to match the other MiniMax models

* model : add logits mask as MiniMax-Text-01 embeddings tensor has zero-valued embeddings for tokens >= 200032 that produce zero logits disrupting the token sampling process

* llama : replace hardcoded conditions with hparams.is_recr()

* model : used build_rs() for recurrent state management

* chore : code cleanup

* model : optimized MiniMax-Text-01 by removing the state tranpose operations

* chore : removed unnecessary ggml_cont() in MiniMax-Text-01 implementation

* llama : add generic logits mask graph input

* model : permuted diag_decay dimensions to avoid doing it inside MiniMax-Text-01 graph

* chore : code cleanup

* chore : code cleanup

* model : use token positions when calculating MiniMax-Text-01 decay tensors

* convert : add support for MiniMaxM1ForCausalLM as it seems to be the same as MiniMaxText01ForCausalLM

* chat : add jinja template for MiniMax-M1

Co-authored-by: QscQ <qscqesze@gmail.com>

* chore : code cleanup

* tests : MINIMAX_01-related fixes

* chore : silence Python lint errors

* vocab : remove unnecessary vocab type

* convert : update MiniMaxText01Model conversion to use yield when modifying tensors

* convert : suppress tokens with zero-valued embeddings during MiniMax-Text-01 conversion

* llama : removed logits mask - no longer necessary as token suppression is used instead

* model : use common functions to make MiniMax-Text-01 implementation more concise

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>

* model : use common functions to make MiniMax-Text-01 implementation more concise

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>

* convert : override non-working built-in chat template during conversion

* tests : skip arch MINIMAX_01 tests for WebGPU backend (it breaks again)

---------

Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
Co-authored-by: QscQ <qscqesze@gmail.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>

gguf-py/gguf/tensor_mapping.py

@@ -225,6 +225,7 @@ class TensorNameMap:
             "rwkv.blocks.{bid}.ln2",                        # rwkv6
             "model.layers.{bid}.ln2",                       # rwkv7
             "model.layers.{bid}.post_attention_layernorm",  # cogvlm
+            "model.layers.{bid}.self_attn.norm",            # minimax-01
         ),
 
         # Attention query-key-value
@@ -321,7 +322,7 @@ class TensorNameMap:
             "h.{bid}.self_attention.dense",                                 # bloom
             "model.layers.{bid}.self_attn.o_proj",                          # llama-hf nemotron olmoe olmo2 phimoe
             "layers.{bid}.self_attn.o_proj",                                # embeddinggemma
-            "model.layers.{bid}.self_attn.out_proj",                        # lfm2
+            "model.layers.{bid}.self_attn.out_proj",                        # lfm2 minimax-01
             "model.layers.{bid}.self_attn.linear_attn",                     # deci
             "layers.{bid}.attention.wo",                                    # llama-pth
             "encoder.layer.{bid}.attention.output.dense",                   # bert
@@ -385,6 +386,7 @@ class TensorNameMap:
             "model.layers.{bid}.self_attn.gate_proj", # afmoe muse-glimmer
             "model.layers.{bid}.linear_attn.in_proj_z",  # qwen3.5
             "model.layers.{bid}.self_attn.g_proj",    # step3.5 head-wise attention gate
+            "model.layers.{bid}.self_attn.output_gate",  # minimax-01
         ),
 
         # Feed-forward norm