Update README.md

README.md

@@ -29,10 +29,23 @@ The model has ~354M parameters and a vocabulary of 50.335 tokens. It is a founda
 
 <h3>Quick usage</h3>
 
-In order to use the model for inference, the following pipeline is needed:
+In order to use the model for inference on GPU, the following pipeline is needed:
 
 ```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+from transformers import pipeline
 
+tokenizer = AutoTokenizer.from_pretrained("osiria/diablo-italian-base-354m")
+model = AutoModelForCausalLM.from_pretrained("osiria/diablo-italian-base-354m", torch_dtype=torch.float16)
+
+device = torch.device("cuda")
+model = model.to(device)
+
+pipeline_nlg = pipeline("text-generation", model = model, tokenizer = tokenizer, device = 0)
+pipeline_nlg("Ciao, mi chiamo Marco Rossi e")
+
+# [{'generated_text': 'Ciao, mi chiamo Marco Rossi e sono un ragazzo di 23 anni.'}]
 ```