falcon-h1 specefic vocab resolved

convert_hf_to_gguf.py

@@ -4882,9 +4882,6 @@ class Mamba2Model(TextModel):
         pad_vocab = self.hparams.get("pad_vocab_size_multiple", 16)
         # pad using ceiling division
         # ref: https://stackoverflow.com/a/17511341/22827863
-        # if architecture is FalconH1, don't pad vocab size
-        if self.hparams.get("architectures", [None])[0] == "FalconH1ForCausalLM":
-            pad_vocab = 1
         vocab_size = -(vocab_size // -pad_vocab) * pad_vocab
         self.hparams["vocab_size"] = vocab_size
 
@@ -6590,6 +6587,9 @@ class FalconH1Model(Mamba2Model):
         keys = list(keys) + prefixed
         return super().find_hparam(keys, *args, **kwargs)
 
+    def set_vocab(self):
+        self._set_vocab_gpt2()
+
     def _generate_mup_vector(self, block_id: int) -> torch.Tensor:
         zxbcdt_multipliers = self.hparams["ssm_multipliers"]
         intermediate_size = self.hparams["mamba_d_ssm"]