Revert "Always enable safetensors for save_quantized() (huggingface#20)"

This reverts commit 0d1be56.

auto_gptq/modeling/_base.py

@@ -456,6 +456,7 @@ def save_quantized(
         save_dir: str,
         safetensors_metadata: Optional[Dict[str, str]] = None,
         format: Optional[str] = None,
+        use_safetensors: bool = True,
     ):
         """save quantized model and configs to local disk"""
         os.makedirs(save_dir, exist_ok=True)
@@ -522,46 +523,53 @@ def save_quantized(
         model.to(CPU)
 
         if quantize_config.model_file_base_name is None:
-            model_base_name = "model"
+            if use_safetensors:
+                model_base_name = "model"
+            else:
+                model_base_name = "pytorch_model"
         else:
             model_base_name = quantize_config.model_file_base_name
 
-        model_save_name = model_base_name + ".safetensors"
-        state_dict = model.state_dict()
-        state_dict = {k: v.clone().contiguous() for k, v in state_dict.items()}
-        if safetensors_metadata is None:
-            safetensors_metadata = {}
-        elif not isinstance(safetensors_metadata, dict):
-            raise TypeError("safetensors_metadata must be a dictionary.")
-        else:
-            logger.debug(f"Received safetensors_metadata: {safetensors_metadata}")
-            new_safetensors_metadata = {}
-            converted_keys = False
-            for key, value in safetensors_metadata.items():
-                if not isinstance(key, str) or not isinstance(value, str):
-                    converted_keys = True
-                    try:
-                        new_key = str(key)
-                        new_value = str(value)
-                    except Exception as e:
-                        raise TypeError(
-                            f"safetensors_metadata: both keys and values must be strings and an error occured when trying to convert them: {e}"
-                        )
-                    if new_key in new_safetensors_metadata:
-                        logger.warning(
-                            f"After converting safetensors_metadata keys to strings, the key '{new_key}' is duplicated. Ensure that all your metadata keys are strings to avoid overwriting."
-                        )
-                    new_safetensors_metadata[new_key] = new_value
-            safetensors_metadata = new_safetensors_metadata
-            if converted_keys:
-                logger.debug(
-                    f"One or more safetensors_metadata keys or values had to be converted to str(). Final safetensors_metadata: {safetensors_metadata}"
-                )
+        if use_safetensors:
+            model_save_name = model_base_name + ".safetensors"
+            state_dict = model.state_dict()
+            state_dict = {k: v.clone().contiguous() for k, v in state_dict.items()}
+            if safetensors_metadata is None:
+                safetensors_metadata = {}
+            elif not isinstance(safetensors_metadata, dict):
+                raise TypeError("safetensors_metadata must be a dictionary.")
+            else:
+                logger.debug(f"Received safetensors_metadata: {safetensors_metadata}")
+                new_safetensors_metadata = {}
+                converted_keys = False
+                for key, value in safetensors_metadata.items():
+                    if not isinstance(key, str) or not isinstance(value, str):
+                        converted_keys = True
+                        try:
+                            new_key = str(key)
+                            new_value = str(value)
+                        except Exception as e:
+                            raise TypeError(
+                                f"safetensors_metadata: both keys and values must be strings and an error occured when trying to convert them: {e}"
+                            )
+                        if new_key in new_safetensors_metadata:
+                            logger.warning(
+                                f"After converting safetensors_metadata keys to strings, the key '{new_key}' is duplicated. Ensure that all your metadata keys are strings to avoid overwriting."
+                            )
+                        new_safetensors_metadata[new_key] = new_value
+                safetensors_metadata = new_safetensors_metadata
+                if converted_keys:
+                    logger.debug(
+                        f"One or more safetensors_metadata keys or values had to be converted to str(). Final safetensors_metadata: {safetensors_metadata}"
+                    )
 
             # Format is required to enable Accelerate to load the metadata
             # otherwise it raises an OSError
             safetensors_metadata["format"] = "pt"
             safe_save(state_dict, join(save_dir, model_save_name), safetensors_metadata)
+        else:
+            model_save_name = model_base_name + ".bin"
+            torch.save(model.state_dict(), join(save_dir, model_save_name))
 
         config.quantization_config = quantize_config.to_dict()
         config.save_pretrained(save_dir)
@@ -1048,13 +1056,27 @@ def skip(*args, **kwargs):
 
         # Any post-initialization that require device information, for example buffers initialization on device.
         model = autogptq_post_init(model, use_act_order=quantize_config.desc_act)
+
         model.eval()
 
         # == step6: (optional) warmup triton == #
         if use_triton and warmup_triton:
             from ..nn_modules.qlinear.qlinear_tritonv2 import QuantLinear
             QuantLinear.warmup(model, seqlen=model.seqlen)
 
+
+        # == step7: make model compatible with peft
+        # cls.make_sure_compatible_with_peft(
+        #     model,
+        #     use_triton,
+        #     quantize_config.desc_act,
+        #     quantize_config.group_size,
+        #     bits=quantize_config.bits,
+        #     disable_exllama=disable_exllama,
+        #     disable_exllamav2=disable_exllamav2,
+        #     use_marlin=use_marlin,
+        # )
+
         return cls(
             model,
             True,