Update README.md

README.md

@@ -57,7 +57,7 @@ tokenizer = model.tokenizer
 input_text = tokenizer.apply_chat_template(messages, tokenize=False)
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda:0")
 output_ids = model.generate(input_ids, max_length=150)
-print(model.expert_tokenizer(text=input_text).decode(output_ids[0], skip_special_tokens=True))
+print(tokenizer.decode(output_ids[0], skip_special_tokens=True))
 ```
 
 
@@ -73,7 +73,7 @@ tokenizer = model.tokenizer
 input_text = tokenizer.apply_chat_template(messages, tokenize=False)
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(device)
 output_ids = model.generate(input_ids, max_length=250)
-print(model.expert_tokenizer(text=input_text).decode(output_ids[0], skip_special_tokens=True))
+print(tokenizer.decode(output_ids[0], skip_special_tokens=True))
 ```
 
 # Call the Italian expert:
@@ -87,7 +87,7 @@ tokenizer = model.tokenizer
 input_text = tokenizer.apply_chat_template(messages, tokenize=False)
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(device)
 output_ids = model.generate(input_ids ,temperature=0.6, do_sample=True, top_p=0.9,top_k=20, max_length=500)
-print(model.expert_tokenizer(text=input_text).decode(output_ids[0], skip_special_tokens=True))
+print(tokenizer.decode(output_ids[0], skip_special_tokens=True))
 ```
 
 # Call the French expert:
@@ -102,7 +102,7 @@ input_text = tokenizer.apply_chat_template(messages, tokenize=False)
 print(input_text)
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(device)
 output_ids = model.generate(input_ids ,temperature=0.6, do_sample=True, top_p=0.9,top_k=20, max_length=250)
-print(model.expert_tokenizer(text=input_text).decode(output_ids[0], skip_special_tokens=True))
+print(tokenizer.decode(output_ids[0], skip_special_tokens=True))
 ```
 
 # Call the Scandinavian expert:
@@ -116,7 +116,7 @@ tokenizer = model.tokenizer
 input_text = tokenizer.apply_chat_template(messages, tokenize=False)
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(device)
 output_ids = model.generate(input_ids ,temperature=0.1, do_sample=True, top_p=0.9,top_k=20, max_length=250)
-print(model.expert_tokenizer(text=input_text).decode(output_ids[0], skip_special_tokens=True))
+print(tokenizer.decode(output_ids[0], skip_special_tokens=True))
 ```