Doc: loading from config alone does not load the model weights

pytorch_transformers/modeling_bert.py

@@ -578,6 +578,8 @@ BERT_START_DOCSTRING = r"""    The BERT model was proposed in
 
     Parameters:
         config (:class:`~pytorch_transformers.BertConfig`): Model configuration class with all the parameters of the model. 
+            Initializing with a config file does not load the weights associated with the model, only the configuration.
+            Check out the :meth:`~pytorch_transformers.PreTrainedModel.from_pretrained` method to load the model weights.
 """
 
 BERT_INPUTS_DOCSTRING = r"""

pytorch_transformers/modeling_gpt2.py

@@ -383,6 +383,8 @@ GPT2_START_DOCSTRING = r"""    OpenAI GPT-2 model was proposed in
 
     Parameters:
         config (:class:`~pytorch_transformers.GPT2Config`): Model configuration class with all the parameters of the model.
+            Initializing with a config file does not load the weights associated with the model, only the configuration.
+            Check out the :meth:`~pytorch_transformers.PreTrainedModel.from_pretrained` method to load the model weights.
 """
 
 GPT2_INPUTS_DOCSTRING = r"""    Inputs:

pytorch_transformers/modeling_openai.py

@@ -397,6 +397,8 @@ OPENAI_GPT_START_DOCSTRING = r"""    OpenAI GPT model was proposed in
 
     Parameters:
         config (:class:`~pytorch_transformers.OpenAIGPTConfig`): Model configuration class with all the parameters of the model.
+            Initializing with a config file does not load the weights associated with the model, only the configuration.
+            Check out the :meth:`~pytorch_transformers.PreTrainedModel.from_pretrained` method to load the model weights.
 """
 
 OPENAI_GPT_INPUTS_DOCSTRING = r"""    Inputs:

pytorch_transformers/modeling_roberta.py

@@ -90,7 +90,8 @@ ROBERTA_START_DOCSTRING = r"""    The RoBERTa model was proposed in
 
     Parameters:
         config (:class:`~pytorch_transformers.RobertaConfig`): Model configuration class with all the parameters of the 
-            model.
+            model. Initializing with a config file does not load the weights associated with the model, only the configuration.
+            Check out the :meth:`~pytorch_transformers.PreTrainedModel.from_pretrained` method to load the model weights.
 """
 
 ROBERTA_INPUTS_DOCSTRING = r"""

pytorch_transformers/modeling_transfo_xl.py

@@ -928,6 +928,8 @@ TRANSFO_XL_START_DOCSTRING = r"""    The Transformer-XL model was proposed in
 
     Parameters:
         config (:class:`~pytorch_transformers.TransfoXLConfig`): Model configuration class with all the parameters of the model.
+            Initializing with a config file does not load the weights associated with the model, only the configuration.
+            Check out the :meth:`~pytorch_transformers.PreTrainedModel.from_pretrained` method to load the model weights.
 """
 
 TRANSFO_XL_INPUTS_DOCSTRING = r"""

pytorch_transformers/modeling_utils.py

@@ -71,6 +71,10 @@ class PretrainedConfig(object):
     r""" Base class for all configuration classes.
         Handles a few parameters common to all models' configurations as well as methods for loading/downloading/saving configurations.
 
+        Note:
+            A configuration file can be loaded and saved to disk. Loading the configuration file and using this file to initialize a model does **not** load the model weights.
+            It only affects the model's configuration.
+
         Class attributes (overridden by derived classes):
             - ``pretrained_config_archive_map``: a python ``dict`` of with `short-cut-names` (string) as keys and `url` (string) of associated pretrained model configurations as values.
 

pytorch_transformers/modeling_xlm.py

@@ -416,6 +416,8 @@ XLM_START_DOCSTRING = r"""    The XLM model was proposed in
 
     Parameters:
         config (:class:`~pytorch_transformers.XLMConfig`): Model configuration class with all the parameters of the model.
+            Initializing with a config file does not load the weights associated with the model, only the configuration.
+            Check out the :meth:`~pytorch_transformers.PreTrainedModel.from_pretrained` method to load the model weights.
 """
 
 XLM_INPUTS_DOCSTRING = r"""

pytorch_transformers/modeling_xlnet.py

@@ -647,6 +647,8 @@ XLNET_START_DOCSTRING = r"""    The XLNet model was proposed in
 
     Parameters:
         config (:class:`~pytorch_transformers.XLNetConfig`): Model configuration class with all the parameters of the model.
+            Initializing with a config file does not load the weights associated with the model, only the configuration.
+            Check out the :meth:`~pytorch_transformers.PreTrainedModel.from_pretrained` method to load the model weights.
 """
 
 XLNET_INPUTS_DOCSTRING = r"""