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polieste
/
fastAbs_large

Summarization
Transformers
PyTorch
TensorFlow
Vietnamese
t5
text2text-generation
text-generation-inference
Model card Files
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README.md CHANGED
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  ---
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  language: vi
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  datasets:
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- - cc100
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  tags:
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  - summarization
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-
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  license: mit
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-
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  widget:
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- - text: "Input text."
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  ---
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- # ViT5-large Finetuned on `vietnews` Abstractive Summarization
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  ```python
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  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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  ​
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- tokenizer = AutoTokenizer.from_pretrained("VietAI/vit5-large-vietnews-summarization")
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- model = AutoModelForSeq2SeqLM.from_pretrained("VietAI/vit5-large-vietnews-summarization")
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  model.cuda()
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  ​
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  sentence = "Input text"
@@ -34,4 +32,4 @@ outputs = model.generate(
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  for output in outputs:
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  line = tokenizer.decode(output, skip_special_tokens=True, clean_up_tokenization_spaces=True)
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  print(line)
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- ```
 
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  ---
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  language: vi
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  datasets:
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+ - Yuhthe/vietnews
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  tags:
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  - summarization
 
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  license: mit
 
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  widget:
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+ - text: Input text.
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  ---
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+ # fastAbs-large Finetuned on `vietnews` Abstractive Summarization
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  ```python
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  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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  ​
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+ tokenizer = AutoTokenizer.from_pretrained("polieste/fastAbs_large")
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+ model = AutoModelForSeq2SeqLM.from_pretrained("polieste/fastAbs_large")
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  model.cuda()
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  ​
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  sentence = "Input text"
 
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  for output in outputs:
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  line = tokenizer.decode(output, skip_special_tokens=True, clean_up_tokenization_spaces=True)
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  print(line)
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+ ```