diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py
index f601f3277a..67ce07e17e 100755
--- a/convert_hf_to_gguf.py
+++ b/convert_hf_to_gguf.py
@@ -6665,7 +6665,6 @@ class FalconH1Model(Mamba2Model):
         self.gguf_writer.add_layer_norm_rms_eps(self.hparams["rms_norm_eps"])
         self.gguf_writer.add_key_length(self.hparams["head_dim"])
         self.gguf_writer.add_value_length(self.hparams["head_dim"])
-        self.gguf_writer.add_float64("falcon_h1.key_multiplier", self.hparams["key_multiplier"])
 
         ## Validation ##
         assert self.hparams.get("hidden_act") in [None, "silu"], "Only SILU activation supported"
@@ -6673,17 +6672,16 @@ class FalconH1Model(Mamba2Model):
 
 
         # Add Falcon Mamba2 specific configuration
-        self.gguf_writer.add_uint32("falcon_h1.attention.head_dim", self.hparams["head_dim"])
-        self.gguf_writer.add_uint32("falcon_h1.ssm.mamba_d_inner", self.hparams["mamba_d_ssm"])
+        self.gguf_writer.add_ssm_head_dim(self.hparams["mamba_d_head"])
         self.gguf_writer.add_ssm_inner_size(self.hparams["mamba_d_ssm"])
-        self.gguf_writer.add_uint32("falcon_h1.num_attention_heads", self.find_hparam(["num_attention_heads"]))
-        self.gguf_writer.add_uint32("falcon_h1.num_key_value_heads", 
-                                    self.find_hparam(["num_key_value_heads"], optional=True) or 
-                                    self.find_hparam(["num_attention_heads"]))
+        self.gguf_writer.add_head_count(self.find_hparam(["num_attention_heads"]))
+        self.gguf_writer.add_key_length(self.hparams["head_dim"])
+        self.gguf_writer.add_value_length(self.hparams["head_dim"])
+        self.gguf_writer.add_head_count_kv(self.find_hparam(["num_key_value_heads"], optional=True) or 
+            self.find_hparam(["num_attention_heads"]))
 
 
         # Add any other Falcon Mamba2 specific configuration
-        self.gguf_writer.add_bool("falcon_h1.mamba_rms_norm", self.find_hparam(["mamba_rms_norm"], optional=True))
         self.gguf_writer.add_rope_freq_base(self.find_hparam(["rope_theta"]))
 
 ###### CONVERSION LOGIC ######
diff --git a/src/llama-arch.cpp b/src/llama-arch.cpp
index 46eeea814f..af8d89eadc 100644
--- a/src/llama-arch.cpp
+++ b/src/llama-arch.cpp
@@ -128,8 +128,7 @@ static const std::map<llm_kv, const char *> LLM_KV_NAMES = {
     { LLM_KV_EMBEDDING_SCALE,                   "%s.embedding_scale"                   },
     { LLM_KV_TOKEN_SHIFT_COUNT,                 "%s.token_shift_count"                 },
     { LLM_KV_INTERLEAVE_MOE_LAYER_STEP,         "%s.interleave_moe_layer_step"         },
-    { LLM_KV_ATTN_HEAD_DIM,                     "%s.attention.head_dim"                },
-
+    
     { LLM_KV_ATTENTION_HEAD_COUNT,                   "%s.attention.head_count"                   },
     { LLM_KV_ATTENTION_HEAD_COUNT_KV,                "%s.attention.head_count_kv"                },
     { LLM_KV_ATTENTION_MAX_ALIBI_BIAS,               "%s.attention.max_alibi_bias"               },
diff --git a/src/llama-model.cpp b/src/llama-model.cpp
index 140ec5b8e7..08fb392603 100644
--- a/src/llama-model.cpp
+++ b/src/llama-model.cpp
@@ -1560,7 +1560,6 @@ void llama_model::load_hparams(llama_model_loader & ml) {
                 ml.get_key(LLM_KV_SSM_STATE_SIZE,     hparams.ssm_d_state);
                 ml.get_key(LLM_KV_SSM_TIME_STEP_RANK, hparams.ssm_dt_rank);
                 ml.get_key(LLM_KV_SSM_GROUP_COUNT,    hparams.ssm_n_group);
-                ml.get_key(LLM_KV_SSM_HEAD_DIM,       hparams.ssm_head_dim);
 
                 std::fill(hparams.recurrent_layer_arr.begin(), hparams.recurrent_layer_arr.end(), true);