Update README.md

README.md

@@ -1,3 +1,26 @@
 ---
 license: apache-2.0
 ---
+
+
+This model can be used to generate a SMILES string from an input caption.
+
+## Example Usage
+```python
+from transformers import T5Tokenizer, T5ForConditionalGeneration
+tokenizer = T5Tokenizer.from_pretrained("laituan245/molt5-small-caption2smiles", model_max_length=512)
+model = T5ForConditionalGeneration.from_pretrained('laituan245/molt5-small-caption2smiles')
+input_text = 'The molecule is a monomethoxybenzene that is 2-methoxyphenol substituted by a hydroxymethyl group at position 4. It has a role as a plant metabolite. It is a member of guaiacols and a member of benzyl alcohols.'
+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))
+# The model will generate "COC1=C(C=CC(=C1)CCCO)O". The ground-truth is "COC1=C(C=CC(=C1)CO)O".
+```
+
+## 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*