Update config.py

Signed-off-by: 汪志鹏 <[email protected]>

Author: princepride

vllm/transformers_utils/config.py

@@ -686,9 +686,54 @@ def recurse_elems(elem: Any):
     config_dict["hidden_act"] = config_dict.get("activation", "silu")
     config_dict["tie_word_embeddings"] = config_dict.get(
         "tie_embeddings", False)
-    config_dict["max_seq_len"] = config_dict.get("max_seq_len", 128_000)
-    config_dict["max_position_embeddings"] = config_dict.get(
-        "max_position_embeddings", 128_000)
+    # Check if max_position_embeddings is in params.json
+    mpe_from_params = config_dict.get("max_position_embeddings")
+    final_mpe_to_set = mpe_from_params
+
+    if final_mpe_to_set is None:
+        # Not found in params.json, try to get from standard HF AutoConfig
+        hf_config_for_defaults = None
+        try:
+            trust_remote_code_val = kwargs.get("trust_remote_code", False)
+            token_val = kwargs.get("token")  # Passed from get_config
+
+            hf_config_for_defaults = AutoConfig.from_pretrained(
+                model,
+                revision=revision,
+                trust_remote_code=trust_remote_code_val,
+                token=token_val)
+        except Exception as e:
+            error_message = (
+                "Invalid repository ID or local directory specified:"
+                " '{model}'.\nPlease verify the following requirements:\n"
+                "1. Provide a valid Hugging Face repository ID.\n"
+                "2. Specify a local directory that contains a recognized "
+                "configuration file.\n").format(model=model)
+
+            raise ValueError(error_message) from e
+
+        if hf_config_for_defaults:
+            # Try to get from text_config first, then top-level
+            mpe_from_hf_config = None
+            text_config_obj = getattr(hf_config_for_defaults, "text_config",
+                                      None)
+            if text_config_obj and hasattr(text_config_obj,
+                                           "max_position_embeddings"):
+                mpe_from_hf_config = getattr(text_config_obj,
+                                             "max_position_embeddings", None)
+
+            if mpe_from_hf_config is None and hasattr(
+                    hf_config_for_defaults, "max_position_embeddings"):
+                mpe_from_hf_config = getattr(hf_config_for_defaults,
+                                             "max_position_embeddings", None)
+
+            if mpe_from_hf_config is not None:
+                final_mpe_to_set = mpe_from_hf_config
+
+        if final_mpe_to_set is None:  # Still not found, use ultimate fallback
+            final_mpe_to_set = 128_000
+
+    config_dict["max_position_embeddings"] = final_mpe_to_set
 
     if config_dict.get("quantization") is not None:
         quantization = config_dict.get("quantization", {})