model : BailingMoE3 Support (#26608)

* Adding support for bailingmoe3

* Adds speculative decoding support

* Make BailingMoE3 safe gate metadata optional

* bailingmoe3: apply trained SwiGLU clamps

* common: fix Bailing V3 tool argument parsing

* llama-model-saver, instantiate float vector metadata writer

* bailingmoe3: support Q-LoRA (Ling-3.0-tiny)

Ling-3.0-flash sets q_lora_rank: None and projects Q directly, so the current
implementation loads a single ATTN_Q tensor. Ling-3.0-tiny sets q_lora_rank: 256
and routes Q through a LoRA bottleneck instead:

    q_a_proj -> q_a_layernorm -> q_b_proj

Conversion therefore failed with:

    ValueError: Can not map tensor 'model.layers.3.attention.q_a_layernorm.weight'

Add the missing path, mirroring the existing deepseek2 MLA implementation:

  * constants.py       - add ATTN_Q_A / ATTN_Q_B / ATTN_Q_A_NORM to BAILINGMOE3
  * tensor_mapping.py  - map model.layers.{bid}.attention.q_{a,b}_proj and
                         q_a_layernorm
  * conversion         - emit attention.q_lora_rank when the config has it
  * bailingmoe3.cpp    - read n_lora_q; create the Q-LoRA tensors and build Q
                         through the bottleneck when q_lora_rank > 0

Everything is gated on q_lora_rank > 0. Ling-3.0-flash's config has no
q_lora_rank, the converter only emits the key when present, hparams.n_lora_q
defaults to 0, and get_key(..., required=false) leaves the target untouched when
the key is absent - so flash keeps taking the existing direct-Q branch.

The LoRA path produces the same shape as the direct projection, so the
nope/rope split, RoPE application and wk_b absorption downstream are unchanged.

* small mtp change

* bailingmoe3: support separate MTP GGUF and Q-LoRA MTP

* gguf: remove duplicate add_kda_gate_lower_bound definition

---------

Co-authored-by: bloomer <bloomer@booper.brushtail.me>
Co-authored-by: Dyluhn <dylanranejohnston1@gmail.com>

gguf-py/gguf/gguf_writer.py

@@ -1103,9 +1103,6 @@ class GGUFWriter:
     def add_ssm_dt_b_c_rms(self, value: bool) -> None:
         self.add_bool(Keys.SSM.DT_B_C_RMS.format(arch=self.arch), value)
 
-    def add_kda_gate_lower_bound(self, value: float) -> None:
-        self.add_float32(Keys.KDA.GATE_LOWER_BOUND.format(arch=self.arch), value)
-
     def add_expert_latent_length(self, value: int) -> None:
         self.add_uint32(Keys.LLM.EXPERT_LATENT_LENGTH.format(arch=self.arch), value)
 
@@ -1121,6 +1118,12 @@ class GGUFWriter:
     def add_kda_head_dim(self, value: int) -> None:
         self.add_uint32(Keys.KDA.HEAD_DIM.format(arch=self.arch), value)
 
+    def add_kda_safe_gate(self, value: bool) -> None:
+        self.add_bool(Keys.KDA.SAFE_GATE.format(arch=self.arch), value)
+
+    def add_kda_gate_lower_bound(self, value: float) -> None:
+        self.add_float32(Keys.KDA.GATE_LOWER_BOUND.format(arch=self.arch), value)
+
     def add_tokenizer_model(self, model: str) -> None:
         self.add_string(Keys.Tokenizer.MODEL, model)