diff --git a/server/text_generation_server/layers/fp8.py b/server/text_generation_server/layers/fp8.py
index f7710145..c626ddb8 100644
--- a/server/text_generation_server/layers/fp8.py
+++ b/server/text_generation_server/layers/fp8.py
@@ -165,7 +165,7 @@ class HybridFP8UnquantLoader(WeightsLoader):
             scale = scale.reshape(-1).expand(w.shape[0])
 
             input_scale = None
-            if weights.get_tensor(f"{prefix}.input_scale"):
+            if weights.has_tensor(f"{prefix}.input_scale"):
                 input_scale = weights.get_tensor(
                     f"{prefix}.input_scale", to_dtype=False
                 )
@@ -213,6 +213,7 @@ class HybridFP8UnquantLoader(WeightsLoader):
                 for p, shape in zip(prefixes, shapes)
                 if weights.has_tensor(f"{p}.input_scale")
             ]
+            assert len(input_scale) == 0 or len(input_scale) == len(prefixes)
             input_scale = (
                 torch.cat(input_scale, dim=0).reshape(-1).max()
                 if len(input_scale) != 0
diff --git a/server/text_generation_server/models/__init__.py b/server/text_generation_server/models/__init__.py
index c9886092..7891a15d 100644
--- a/server/text_generation_server/models/__init__.py
+++ b/server/text_generation_server/models/__init__.py
@@ -342,6 +342,7 @@ def get_model(
     model_type = config_dict.get("model_type", None)
 
     quantization_config = config_dict.get("quantization_config", None)
+    compression_config = config_dict.get("compression_config", None)
     if quantization_config is not None and quantize is None:
         method = quantization_config.get("quant_method", None)
         config_groups = quantization_config.get("config_groups", None)
@@ -352,7 +353,6 @@ def get_model(
             log_master(logger.info, "Auto selecting quantization method fp8")
             quantize = "fp8"
         elif config_groups is not None:
-            # Compression config renamed to quantization_config
             # TODO: at some point we should probably fully parse the compression
             # configuration to know which parameters are compressed.
             for _, group in config_groups.items():
@@ -369,6 +369,22 @@ def get_model(
                         break
         else:
             log_master(logger.warning, f"Unknown quantization method {method}")
+    elif compression_config is not None:
+        # For backward compatibility: compression_config is renamed to quantization_config
+        config_groups = compression_config.get("config_groups")
+        if config_groups is not None:
+            for _, group in config_groups.items():
+                weights_config = group.get("weights")
+                if weights_config is not None:
+                    if (
+                        weights_config["type"] == "float"
+                        and weights_config["num_bits"] == 8
+                    ):
+                        log_master(
+                            logger.info, "Auto selecting quantization method fp8"
+                        )
+                        quantize = "fp8"
+                        break
 
     if dtype is None:
         if quantize in ["awq", "exl2", "gptq", "marlin"]: