Update README.md

README.md

@@ -28,20 +28,12 @@ model_id = "Eurdem/Defne_llama3_2x8B"
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto", load_in_8bit= True)
 
-messages = [
-    {"role": "system", "content": "You are a helpful chatbot, named Defne, who always responds friendly."},
-    {"role": "user", "content": "Answer the questions: 1) Who are you? 2) f(x)=3x^2+4x+12 so what is f(3)?"},
+messages = [{"role": "system", "content": "You are a helpful chatbot, named Defne, who always responds friendly."},
+            {"role": "user", "content": "Answer the questions: 1) Who are you? 2) f(x)=3x^2+4x+12 so what is f(3)?"},
 ]
 
 input_ids = tokenizer.apply_chat_template(messages, return_tensors="pt").to("cuda")
-
-outputs = model.generate(input_ids,
-                          max_new_tokens=1024,
-                          do_sample=True,
-                          temperature=0.7,
-                          top_p=0.7,
-                          top_k=500,
-                      )
+outputs = model.generate(input_ids, max_new_tokens=1024, do_sample=True, temperature=0.7, top_p=0.7, top_k=500,)
 response = outputs[0][input_ids.shape[-1]:]
 print(tokenizer.decode(response, skip_special_tokens=True))
 ```
@@ -75,20 +67,12 @@ model_id = "Eurdem/Defne_llama3_2x8B"
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto", load_in_8bit= True)
 
-messages = [
-    {"role": "system", "content": "Sen Defne isimli Türkçe konuşan bir chatbotsun."},
-    {"role": "user", "content": "Sana 2 sorum var. 1) Sen kimsin?  2)f(x)=3x^2+4x+12 ise f(3) kaçtır?"}
+messages = [{"role": "system", "content": "Sen Defne isimli Türkçe konuşan bir chatbotsun."},
+            {"role": "user", "content": "Sana 2 sorum var. 1) Sen kimsin?  2)f(x)=3x^2+4x+12 ise f(3) kaçtır?"}
 ]
 
 input_ids = tokenizer.apply_chat_template(messages, return_tensors="pt").to("cuda")
-
-outputs = model.generate(input_ids,
-                          max_new_tokens=1024,
-                          do_sample=True,
-                          temperature=0.7,
-                          top_p=0.7,
-                          top_k=500,
-                      )
+outputs = model.generate(input_ids, max_new_tokens=1024, do_sample=True, temperature=0.7, top_p=0.7, top_k=500,)
 response = outputs[0][input_ids.shape[-1]:]
 print(tokenizer.decode(response, skip_special_tokens=True))
 ```