uer
/

gpt2-chinese-poem

Text Generation

text-generation-inference

Inference Endpoints

Model card Files Files and versions Community

uer commited on Jan 26, 2021

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7e9daa9

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1 Parent(s): d3552f7

Update README.md

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@@ -21,8 +21,7 @@ You can use the model directly with a pipeline for text generation:
 When the parameter skip_special_tokens is True:
 ```python
->>> from transformers import BertTokenizer, GPT2LMHeadModel, TextGenerationPipeline
->>> from transformers import TextGenerationPipeline,
 >>> tokenizer = BertTokenizer.from_pretrained("uer/gpt2-chinese-poem")
 >>> model = GPT2LMHeadModel.from_pretrained("uer/gpt2-chinese-poem")
 >>> text_generator = TextGenerationPipeline(model, tokenizer)
@@ -33,8 +32,7 @@ When the parameter skip_special_tokens is True:
 When the parameter skip_special_tokens is False:
 ```python
->>> from transformers import BertTokenizer, GPT2LMHeadModel, TextGenerationPipeline
->>> from transformers import TextGenerationPipeline,
 >>> tokenizer = BertTokenizer.from_pretrained("uer/gpt2-chinese-poem")
 >>> model = GPT2LMHeadModel.from_pretrained("uer/gpt2-chinese-poem")
 >>> text_generator = TextGenerationPipeline(model, tokenizer)

 When the parameter skip_special_tokens is True:
 ```python
+>>> from transformers import BertTokenizer, GPT2LMHeadModel,TextGenerationPipeline
 >>> tokenizer = BertTokenizer.from_pretrained("uer/gpt2-chinese-poem")
 >>> model = GPT2LMHeadModel.from_pretrained("uer/gpt2-chinese-poem")
 >>> text_generator = TextGenerationPipeline(model, tokenizer)
 When the parameter skip_special_tokens is False:
 ```python
+>>> from transformers import BertTokenizer, GPT2LMHeadModel,TextGenerationPipeline
 >>> tokenizer = BertTokenizer.from_pretrained("uer/gpt2-chinese-poem")
 >>> model = GPT2LMHeadModel.from_pretrained("uer/gpt2-chinese-poem")
 >>> text_generator = TextGenerationPipeline(model, tokenizer)