[SAVE] Save config files with empty state dict (#1293)

* Save model and config files with empty state dict

* cleanup

* cleanup

Author: ZX-ModelCloud

gptqmodel/models/base.py

@@ -952,7 +952,7 @@ def save(
             meta_quantizer: Optional[str] = None,
             **kwargs,
     ):
-        extra_json_file_names = ["preprocessor_config.json", "chat_template.json"]
+        extra_json_file_names = ["preprocessor_config.json"]
         for name in extra_json_file_names:
             json_path = os.path.join(self.model_local_path, name)
             if os.path.exists(json_path):

gptqmodel/models/writer.py

@@ -29,6 +29,7 @@
 from huggingface_hub import split_torch_state_dict_into_shards
 from huggingface_hub.constants import SAFETENSORS_WEIGHTS_FILE_PATTERN
 from safetensors.torch import save_file as safe_save
+from torch import nn
 from transformers import AutoConfig, PreTrainedTokenizerFast, GenerationConfig
 from transformers.modeling_utils import no_init_weights
 from transformers.models.auto.tokenization_auto import get_tokenizer_config
@@ -305,13 +306,13 @@ def save_quantized(
             logger.info(f"Size difference: {size_diff_mb:.2f}MB, {size_diff_gb:.2f}GB - {percent_diff:.2f}%")
 
         config.quantization_config = quantize_config.to_dict()
-        config.save_pretrained(save_dir)
 
-        quantize_config.save_pretrained(save_dir)
+        self.model.config = config
+
+        # Save config files with empty state dict
+        self.model.save_pretrained(save_dir, state_dict={})
 
-         # check for generation_config(.json)
-        if hasattr(self, "generation_config") and isinstance(self.generation_config, GenerationConfig):
-            self.generation_config.save_pretrained(save_dir)
+        quantize_config.save_pretrained(save_dir)
 
         # need to copy .py files for model/tokenizers not yet merged to HF transformers
         if self.trust_remote_code: