Update README.md

README.md

@@ -22,11 +22,29 @@ and first released at [this page](https://openai.com/blog/better-language-models
 # How to use the model
 
 ~~~~
-from transformers import GPT2Tokenizer, AutoModelForCausalLM
+import torch
+from transformers import GPT2Tokenizer, GPT2LMHeadModel
 
-tokenizer = GPT2Tokenizer.from_pretrained("NlpHUST/gpt2-vietnamese")
+tokenizer = GPT2Tokenizer.from_pretrained('NlpHUST/gpt2-vietnamese')
+model = GPT2LMHeadModel.from_pretrained('NlpHUST/gpt2-vietnamese')
 
-model = AutoModelForCausalLM.from_pretrained("NlpHUST/gpt2-vietnamese")
+text = "Albert Einstein là nhà vật lý học tạo ra thuyết lượng tử"
+input_ids = tokenizer.encode(text, return_tensors='pt')
+max_length = 100
+
+sample_outputs = model.generate(input_ids,pad_token_id=tokenizer.eos_token_id,
+                                   do_sample=True,
+                                   max_length=max_length,
+                                   min_length=max_length,
+                                   top_k=40,
+                                   num_beams=5,
+                                   early_stopping=True,
+                                   no_repeat_ngram_size=2,
+                                   num_return_sequences=3)
+
+for i, sample_output in enumerate(sample_outputs):
+    print(">> Generated text {}\n\n{}".format(i+1, tokenizer.decode(sample_output.tolist())))
+    print('\n---')
 ~~~~
 
 # Model architecture