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good quality generation example for GPT, GPT-2, Transfo-XL, XLNet

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thomwolf
2019-07-13 15:25:03 +02:00
parent 7322c314a6
commit 7d4b200e40
10 changed files with 252 additions and 46 deletions
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8
pytorch_transformers/modeling_gpt2.py
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@@ -37,9 +37,9 @@ 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_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"}
def load_tf_weights_in_gpt2(model, config, gpt2_checkpoint_path):
""" Load tf checkpoints in a pytorch model
@@ -195,6 +195,10 @@ class GPT2Config(PretrainedConfig):
"or the path to a pretrained model config file (str)"
)
@property
def max_position_embeddings(self):
return self.n_positions
@property
def hidden_size(self):
return self.n_embd