use path for HFLM

scripts/eval.py

@@ -227,22 +227,15 @@ def load_custom_model(args) -> HFLM:
             "float32": torch.float32
         }[args.dtype]
     
-    # Load the custom model
-    hf_model = MyOlmoeForCausalLM.from_pretrained(
-        args.model_path,
-        config=config,
-        torch_dtype=torch_dtype,
-        device_map="auto" if args.device == "auto" else None,
-        trust_remote_code=args.trust_remote_code
-    ).eval()
     
     # Wrap in HFLM
     model = HFLM(
-        pretrained=hf_model,
+        pretrained=args.model_path,
         device=args.device,
         batch_size=args.batch_size,
         max_batch_size=args.max_batch_size,
-        dtype=args.dtype
+        dtype=args.dtype,
+        trust_remote_code=args.trust_remote_code
     )
     
     logger.info("Custom model loaded successfully")