adding gpt-2 large

pytorch_transformers/convert_gpt2_checkpoint_to_pytorch.py

@@ -35,7 +35,7 @@ def convert_gpt2_checkpoint_to_pytorch(gpt2_checkpoint_path, gpt2_config_file, p
     if gpt2_config_file == "":
         config = GPT2Config()
     else:
-        config = GPT2Config(gpt2_config_file)
+        config = GPT2Config.from_json_file(gpt2_config_file)
     model = GPT2Model(config)
 
     # Load weights from numpy

pytorch_transformers/convert_openai_checkpoint_to_pytorch.py

@@ -35,7 +35,7 @@ def convert_openai_checkpoint_to_pytorch(openai_checkpoint_folder_path, openai_c
     if openai_config_file == "":
         config = OpenAIGPTConfig()
     else:
-        config = OpenAIGPTConfig(openai_config_file)
+        config = OpenAIGPTConfig.from_json_file(openai_config_file)
     model = OpenAIGPTModel(config)
 
     # Load weights from numpy

pytorch_transformers/convert_transfo_xl_checkpoint_to_pytorch.py

@@ -75,7 +75,7 @@ def convert_transfo_xl_checkpoint_to_pytorch(tf_checkpoint_path,
         if transfo_xl_config_file == "":
             config = TransfoXLConfig()
         else:
-            config = TransfoXLConfig(transfo_xl_config_file)
+            config = TransfoXLConfig.from_json_file(transfo_xl_config_file)
         print("Building PyTorch model from configuration: {}".format(str(config)))
         model = TransfoXLLMHeadModel(config)
 

pytorch_transformers/modeling_gpt2.py

@@ -38,9 +38,11 @@ from .modeling_bert import BertLayerNorm as LayerNorm
 logger = logging.getLogger(__name__)
 
 GPT2_PRETRAINED_MODEL_ARCHIVE_MAP = {"gpt2": "https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-pytorch_model.bin",
-                                     "gpt2-medium": "https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-medium-pytorch_model.bin"}
+                                     "gpt2-medium": "https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-medium-pytorch_model.bin",
+                                     "gpt2-large": "https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-large-pytorch_model.bin"}
 GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP = {"gpt2": "https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-config.json",
-                                      "gpt2-medium": "https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-medium-config.json"}
+                                      "gpt2-medium": "https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-medium-config.json",
+                                      "gpt2-large": "https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-large-config.json"}
 
 def load_tf_weights_in_gpt2(model, config, gpt2_checkpoint_path):
     """ Load tf checkpoints in a pytorch model

pytorch_transformers/tokenization_gpt2.py

@@ -45,11 +45,13 @@ PRETRAINED_VOCAB_FILES_MAP = {
     {
         'gpt2': "https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-vocab.json",
         'gpt2-medium': "https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-medium-vocab.json",
+        'gpt2-large': "https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-large-vocab.json",
     },
     'merges_file':
     {
         'gpt2': "https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-merges.txt",
         'gpt2-medium': "https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-medium-merges.txt",
+        'gpt2-large': "https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-large-merges.txt",
     },
 }