adding usage example

README.md

@@ -4,8 +4,28 @@ license: lgpl-3.0
 
 # t5_interpreter
 
-A rut5-based model for incomplete utterance restoration, spellchecking and text normalization for conversation system.
+A rut5-based model for incomplete utterance restoration, spellchecking and text normalization for dialogue utterances.
 
+Read more about the task [here](https://huggingface.co/inkoziev/rugpt_interpreter).
+
+
+# Usage example
+
+```
+import torch
+from transformers import T5ForConditionalGeneration, T5Tokenizer
+
+model_name = 'inkoziev/t5_interpreter'
+tokenizer = T5Tokenizer.from_pretrained(model_name,)
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model = T5ForConditionalGeneration.from_pretrained(model_name)
+model.eval()
+
+t5_input = '- Тебя как зовут?\n- Мальвина #'
+input_ids = tokenizer(t5_input, return_tensors='pt').input_ids
+out_ids = model.generate(input_ids=input_ids, max_length=40, eos_token_id=tokenizer.eos_token_id, early_stopping=True)
+t5_output = tokenizer.decode(out_ids[0][1:])
+print(t5_output)
+```
 
-<<<...mode information coming soon...>>>