readme: ---
  license: apache-2.0
  ---
  
  
  This model can be used to generate an input caption from a SMILES string.
  
  ## Example Usage
  ```python
  from transformers import T5Tokenizer, T5ForConditionalGeneration
  
  tokenizer = T5Tokenizer.from_pretrained("laituan245/molt5-base-smiles2caption", model_max_length=512)
  model = T5ForConditionalGeneration.from_pretrained('laituan245/molt5-base-smiles2caption')
  
  input_text = 'C1=CC2=C(C(=C1)[O-])NC(=CC2=O)C(=O)O'
  input_ids = tokenizer(input_text, return_tensors="pt").input_ids
  
  outputs = model.generate(input_ids, num_beams=5, max_length=512)
  print(tokenizer.decode(outputs[0], skip_special_tokens=True))
  ```
  
  ## Paper
  
  For more information, please take a look at our paper.
  
  Paper: [Translation between Molecules and Natural Language](https://arxiv.org/abs/2204.11817)
  
  Authors: *Carl Edwards\*, Tuan Lai\*, Kevin Ros, Garrett Honke, Heng Ji* 
  