fix: correct EXAONE3 FFN_DOWN tensor mapping prefix

The EXAONE3 FFN_DOWN mapping used prefix "model.layers.h.{bid}.mlp.c_proj"
which is incorrect — EXAONE uses "transformer.h.{bid}.mlp.c_proj" prefix
(matching gpt2/refact/qwen/jais). The correct mapping already exists on
a different line but without the "exaone" comment tag.

This fix:
- Removes the dead/unreachable mapping with wrong prefix "model.layers.h."
- Adds "exaone" tag to the existing correct mapping for documentation

The wrong mapping was never hit at runtime because EXAONE weights use
"transformer.h.{bid}.mlp.c_proj" which was already mapped, but the
dead entry is misleading and could cause confusion.

Signed-off-by: User <user@example.com>
Signed-off-by: Bias92 <pewpewplay315@gmail.com>

gguf-py/gguf/tensor_mapping.py

@@ -574,7 +574,7 @@ class TensorNameMap:
         # Feed-forward down
         MODEL_TENSOR.FFN_DOWN: (
             "gpt_neox.layers.{bid}.mlp.dense_4h_to_h",                # gptneox
-            "transformer.h.{bid}.mlp.c_proj",                         # gpt2 refact qwen jais
+            "transformer.h.{bid}.mlp.c_proj",                         # gpt2 refact qwen jais exaone
             "transformer.blocks.{bid}.ffn.down_proj",                 # mpt
             "transformer.h.{bid}.mlp.dense_4h_to_h",                  # falcon
             "h.{bid}.mlp.dense_4h_to_h",                              # bloom
@@ -599,7 +599,6 @@ class TensorNameMap:
             "model.layers.{bid}.residual_mlp.w2",                     # arctic
             "encoder.layer.{bid}.mlp.down_layer",                     # jina-bert-v2
             "encoder.layers.{bid}.mlp.dense_4h_to_h",                 # chatglm
-            "model.layers.h.{bid}.mlp.c_proj",                        # exaone
             "model.layers.{bid}.feed_forward.down_proj",              # llama4 jamba granite-hybrid
             "transformer_encoder.{bid}.ffn.w3",                       # neobert
             "model.layers.{bid}.block_sparse_moe.down",               # smallthinker