English-Simile-Generation is a seq2seq paraphrase model which can transform sentence A to sentence B containing figurative or simile expression.

A： Now I feel sad to see your scientific research progress is so slow.

B： Now I feel sad to see your scientific research progress is as slow as snail.

**To our knowledge, our model have better performance,diversity and practicability compared to EMNLP21 paper (Generating similes effortlessly like a Pro:
A Style Transfer Approach for Simile Generation). **

      from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
      tokenizer = AutoTokenizer.from_pretrained("figurative-nlp/English-Simile-Generation")
      model = AutoModelForSeq2SeqLM.from_pretrained("figurative-nlp/Ehinese-Simile-Generation")
      
      
      input_ids = tokenizer(
          "Adrenaline shot through him powerful", return_tensors="pt"
      ).input_ids
      outputs = model.generate(input_ids,num_beams = 5,max_length = 64)
      result = tokenizer.decode(outputs[0], skip_special_tokens=True)
      print(result)
      #result : Adrenaline shot through him like an electric current
{}
transformers pytorch bart text2text-generation autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bart #text2text-generation #autotrain_compatible #endpoints_compatible #region-us 

English-Simile-Generation is a seq2seq paraphrase model which can transform sentence A to sentence B containing figurative or simile expression.

A： Now I feel sad to see your scientific research progress is so slow.

B： Now I feel sad to see your scientific research progress is as slow as snail.

To our knowledge, our model have better performance,diversity and practicability compared to EMNLP21 paper (Generating similes effortlessly like a Pro:
A Style Transfer Approach for Simile Generation). 

      from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
      tokenizer = AutoTokenizer.from_pretrained("figurative-nlp/English-Simile-Generation")
      model = AutoModelForSeq2SeqLM.from_pretrained("figurative-nlp/Ehinese-Simile-Generation")
      
      
      input_ids = tokenizer(
          "Adrenaline shot through him powerful", return_tensors="pt"
      ).input_ids
      outputs = model.generate(input_ids,num_beams = 5,max_length = 64)
      result = URL(outputs[0], skip_special_tokens=True)
      print(result)
      #result : Adrenaline shot through him like an electric current
TAGS
#transformers #pytorch #bart #text2text-generation #autotrain_compatible #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #bart #text2text-generation #autotrain_compatible #endpoints_compatible #region-us 
