diff --git a/server/text_generation_server/utils/adapter.py b/server/text_generation_server/utils/adapter.py
index 9f6d4960..76a87ad7 100644
--- a/server/text_generation_server/utils/adapter.py
+++ b/server/text_generation_server/utils/adapter.py
@@ -4,6 +4,7 @@ from pathlib import Path
 from typing import List, Dict, Set, Tuple
 
 import torch
+from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE
 from loguru import logger
 from peft import LoraConfig
 from peft.utils import transpose
@@ -76,7 +77,8 @@ def create_merged_weight_files(
     
     adapter_config = LoraConfig.from_pretrained(adapter_id)
     if adapter_config.base_model_name_or_path != model_id:
-        raise ValueError(f"Adapter {adapter_id} is not compatible with model {model_id}")
+        raise ValueError(f"Adapter '{adapter_id}' is not compatible with model '{model_id}'. "
+                         f"Use --model-id '{adapter_config.base_model_name_or_path}' instead.")
     
     # load adapter weights from all shards (should have relatively small memory footprint)
     adapter_weights = {}
@@ -84,15 +86,21 @@ def create_merged_weight_files(
         adapter_weights.update(load_file(filename))
     remaining_adapter_weight_names = set(adapter_weights.keys())
 
-    merged_weight_directory = f"/data/{adapter_id.replace('/', '--')}-merged/"
+    merged_weight_directory = Path(HUGGINGFACE_HUB_CACHE) / f"models--{adapter_id.replace('/', '--')}-merged"
     # just grab the existing files if they already exist and return immediately
     if os.path.exists(merged_weight_directory):
         logger.info("Merged weight files already exist, skipping merge computation.")
         return weight_files(merged_weight_directory)
+    else:
+        logger.info("Merged weight files do not exist, computing merge.")
+        os.makedirs(merged_weight_directory)
 
-    os.makedirs(merged_weight_directory)
     merged_weight_filenames = []
-    for filename in model_weight_filenames:
+    for i, filename in enumerate(model_weight_filenames):
+        logger.info(
+            f"Merging adapter weights into model weights in "
+            f"{filename} ({i+1} / {len(model_weight_filenames)})..."
+        )
         model_weights = load_file(filename)
         merged_weights, processed_adapter_weight_names = merge_adapter_weights(
             model_weights, adapter_weights, adapter_config)
@@ -110,6 +118,8 @@ def create_merged_weight_files(
         for lora_name in remaining_adapter_weight_names:
             logger.warning("\t" + lora_name)
 
+    logger.info(
+        f"Finished merging adapter weights. Merged weight files saved to: {merged_weight_directory}")
     return merged_weight_filenames