Update README.md

README.md

@@ -21,29 +21,28 @@ This is the model for abstractive summarization for Russian based on [rut5-base]
 
 #### How to use
 
-```python
-from transformers import T5Tokenizer, T5ForConditionalGeneration
+Colab: [link](https://colab.research.google.com/drive/1re5E26ZIDUpAx1gOCZkbF3hcwjozmgG0)
 
-article_text = "..."
+```python
+from transformers import AutoTokenizer, T5ForConditionalGeneration
 
 model_name = "IlyaGusev/rut5-base-sum-gazeta"
-tokenizer = T5Tokenizer.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = T5ForConditionalGeneration.from_pretrained(model_name)
 
+article_text = ".."
+
 input_ids = tokenizer(
     [article_text],
     add_special_tokens=True,
     padding="max_length",
     truncation=True,
-    max_length=400,
     return_tensors="pt"
 )["input_ids"]
 
 output_ids = model.generate(
     input_ids=input_ids,
-    max_length=200,
     no_repeat_ngram_size=3,
-    num_beams=5,
     early_stopping=True
 )[0]