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gpt2-chinese-couplet

Text Generation
Transformers
PyTorch
TensorFlow
JAX
Chinese
gpt2
text-generation-inference
Inference Endpoints
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@@ -21,7 +21,6 @@ When the parameter skip_special_tokens is True:
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  ```python
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  >>> from transformers import BertTokenizer, GPT2LMHeadModel, TextGenerationPipeline
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- >>> from transformers import TextGenerationPipeline,
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  >>> tokenizer = BertTokenizer.from_pretrained("uer/gpt2-chinese-couplet")
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  >>> model = GPT2LMHeadModel.from_pretrained("uer/gpt2-chinese-couplet")
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  >>> text_generator = TextGenerationPipeline(model, tokenizer)
@@ -33,7 +32,6 @@ When the parameter skip_special_tokens is False:
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  ```python
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  >>> from transformers import BertTokenizer, GPT2LMHeadModel, TextGenerationPipeline
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- >>> from transformers import TextGenerationPipeline,
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  >>> tokenizer = BertTokenizer.from_pretrained("uer/gpt2-chinese-poem")
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  >>> model = GPT2LMHeadModel.from_pretrained("uer/gpt2-chinese-poem")
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  >>> text_generator = TextGenerationPipeline(model, tokenizer)
 
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  ```python
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  >>> from transformers import BertTokenizer, GPT2LMHeadModel, TextGenerationPipeline
 
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  >>> tokenizer = BertTokenizer.from_pretrained("uer/gpt2-chinese-couplet")
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  >>> model = GPT2LMHeadModel.from_pretrained("uer/gpt2-chinese-couplet")
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  >>> text_generator = TextGenerationPipeline(model, tokenizer)
 
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  ```python
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  >>> from transformers import BertTokenizer, GPT2LMHeadModel, TextGenerationPipeline
 
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  >>> tokenizer = BertTokenizer.from_pretrained("uer/gpt2-chinese-poem")
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  >>> model = GPT2LMHeadModel.from_pretrained("uer/gpt2-chinese-poem")
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  >>> text_generator = TextGenerationPipeline(model, tokenizer)