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roberta_gpt2_summarization_cnn_dailymail

Text2Text Generation Transformers PyTorch TensorBoard
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@@ -26,28 +26,20 @@ RougeL= 23.499
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  ## Intended uses & limitations
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  To use its API:
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- from transformers import BertTokenizerFast, GPT2Tokenizer, EncoderDecoderModel
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  model = EncoderDecoderModel.from_pretrained("Ayham/roberta_gpt2_summarization_cnn_dailymail")
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- input_tokenizer = BertTokenizerFast.from_pretrained('bert-base-cased')
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  article = """Your Input Text"""
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  input_ids = input_tokenizer(article, return_tensors="pt").input_ids
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  output_ids = model.generate(input_ids)
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- output_tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
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  print(output_tokenizer.decode(output_ids[0], skip_special_tokens=True))
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  More information needed
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  ## Intended uses & limitations
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  To use its API:
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+ from transformers import RobertaTokenizerFast, GPT2Tokenizer, EncoderDecoderModel
 
 
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  model = EncoderDecoderModel.from_pretrained("Ayham/roberta_gpt2_summarization_cnn_dailymail")
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+ input_tokenizer = RobertaTokenizerFast.from_pretrained('roberta-base')
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+ output_tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
 
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  article = """Your Input Text"""
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  input_ids = input_tokenizer(article, return_tensors="pt").input_ids
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  output_ids = model.generate(input_ids)
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  print(output_tokenizer.decode(output_ids[0], skip_special_tokens=True))
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  More information needed