[Model] Add support for IBM Granite Code models (#4636)

vllm/model_executor/models/llama.py

@@ -58,15 +58,16 @@ class LlamaMLP(nn.Module):
         intermediate_size: int,
         hidden_act: str,
         quant_config: Optional[QKVParallelLinear] = None,
+        bias: bool = False,
     ) -> None:
         super().__init__()
         self.gate_up_proj = MergedColumnParallelLinear(
             hidden_size, [intermediate_size] * 2,
-            bias=False,
+            bias=bias,
             quant_config=quant_config)
         self.down_proj = RowParallelLinear(intermediate_size,
                                            hidden_size,
-                                           bias=False,
+                                           bias=bias,
                                            quant_config=quant_config)
         if hidden_act != "silu":
             raise ValueError(f"Unsupported activation: {hidden_act}. "
@@ -209,6 +210,7 @@ class LlamaDecoderLayer(nn.Module):
             intermediate_size=config.intermediate_size,
             hidden_act=config.hidden_act,
             quant_config=quant_config,
+            bias=getattr(config, "mlp_bias", False),
         )
         self.input_layernorm = RMSNorm(config.hidden_size,
                                        eps=config.rms_norm_eps)
@@ -348,6 +350,8 @@ class LlamaForCausalLM(nn.Module):
             # compatibility
             if not lora_config else lora_config.lora_vocab_padding_size,
         )
+        if config.tie_word_embeddings:
+            self.lm_head.weight = self.model.embed_tokens.weight
 
         logit_scale = getattr(config, "logit_scale", 1.0)
         self.logits_processor = LogitsProcessor(self.unpadded_vocab_size,