[Misc] Update to comply with the new compressed-tensors config

tests/quantization/test_compressed_tensors.py

@@ -11,8 +11,10 @@
 
 
 def test_compressed_tensors_w8a8_static_setup(vllm_runner):
-    model_path = "nm-testing/tinyllama-one-shot-static-quant-test-compressed"
-    llm = vllm_runner(model_path, quantization="sparseml", enforce_eager=True)
+    model_path = "nm-testing/tinyllama-oneshot-w8a8-static-v2"
+    llm = vllm_runner(model_path,
+                      quantization="compressed-tensors",
+                      enforce_eager=True)
     model = llm.model.llm_engine.model_executor.driver_worker.model_runner.model
     layer = model.model.layers[0]
 
@@ -38,9 +40,9 @@ def test_compressed_tensors_w8a8_static_setup(vllm_runner):
 
 
 def test_compressed_tensors_w8a8_dynanmic_per_token(vllm_runner):
-    model_path = "nm-testing/tinyllama-one-shot-dynamic-test"
+    model_path = "nm-testing/tinyllama-oneshot-w8a8-dynamic-token-v2"
     llm = vllm_runner(model_path,
-                      quantization="sparseml",
+                      quantization="compressed-tensors",
                       enforce_eager=True,
                       dtype=torch.float16)
     model = llm.model.llm_engine.model_executor.driver_worker.model_runner.model

vllm/config.py

@@ -164,12 +164,8 @@ def _verify_embedding_mode(self) -> None:
     def _parse_quant_hf_config(self):
         quant_cfg = getattr(self.hf_config, "quantization_config", None)
         if quant_cfg is None:
-            # SparseML uses a "compression_config" with a "quantization_config".
-            compression_cfg = getattr(self.hf_config, "compression_config",
-                                      None)
-            if compression_cfg is not None:
-                quant_cfg = compression_cfg.get("quantization_config", None)
-
+            # SparseML uses a "compression_config" key
+            quant_cfg = getattr(self.hf_config, "compression_config", None)
         return quant_cfg
 
     def _verify_quantization(self) -> None:

vllm/model_executor/layers/quantization/__init__.py

@@ -31,7 +31,7 @@
     "gptq_marlin": GPTQMarlinConfig,
     "gptq": GPTQConfig,
     "squeezellm": SqueezeLLMConfig,
-    "sparseml": CompressedTensorsConfig,
+    "compressed-tensors": CompressedTensorsConfig,
     "bitsandbytes": BitsAndBytesConfig,
 }
 

vllm/model_executor/model_loader/weight_utils.py

@@ -122,12 +122,8 @@ def get_quant_config(model_config: ModelConfig,
     hf_quant_config = getattr(model_config.hf_config, "quantization_config",
                               None)
     if hf_quant_config is None:
-        compression_config = getattr(model_config.hf_config,
-                                     "compression_config", None)
-        if compression_config is not None:
-            hf_quant_config = compression_config.get("quantization_config",
-                                                     None)
-
+        hf_quant_config = getattr(model_config.hf_config, "compression_config",
+                                  None)
     if hf_quant_config is not None:
         return quant_cls.from_config(hf_quant_config)
     # In case of bitsandbytes/QLoRA, get quant config from the adapter model.