Update README.md

from transformers import GPT2LMHeadModel, GPT2Tokenizer
model_name_or_path = "sberbank-ai/rugpt3large_based_on_gpt2" (можно использовать sberbank-ai/rugpt3xl)
tokenizer = GPT2Tokenizer.from_pretrained(model_name_or_path)
model = GPT2LMHeadModel.from_pretrained(model_name_or_path).cpu()
text = "Иисус Христос родился в "
input_ids = tokenizer.encode(text, return_tensors="pt").cpu()
out = model.generate(input_ids.cpu())
print(generated_text)
generated_text = list(map(tokenizer.decode, out))[0]
print(generated_text)

README.md

@@ -14,3 +14,14 @@ Model was trained with 512 sequence length using [Deepspeed](https://github.com/
 Total training time was around 10 days on 256 GPUs.  
 Final perplexity on test set is `12.05`.
 Model parameters: 1.3B.
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+model_name_or_path = "sberbank-ai/rugpt3large_based_on_gpt2"    (можно использовать sberbank-ai/rugpt3xl)
+tokenizer = GPT2Tokenizer.from_pretrained(model_name_or_path)
+model = GPT2LMHeadModel.from_pretrained(model_name_or_path).cpu()
+text = "Иисус Христос родился в "
+input_ids = tokenizer.encode(text, return_tensors="pt").cpu()
+out = model.generate(input_ids.cpu())
+print(generated_text)
+generated_text = list(map(tokenizer.decode, out))[0]
+print(generated_text)
+