Update README.md (#3)

- Update README.md (ae0f58f719f3b4e4c46f1f3188f2246bb73070fe)

README.md

@@ -109,7 +109,10 @@ print(tokenizer.decode(outputs[0]))
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
 tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-27b-it")
-model = AutoModelForCausalLM.from_pretrained("google/gemma-2-27b-it", device_map="auto", torch_dtype=torch.bfloat16)
+model = AutoModelForCausalLM.from_pretrained(
+    "google/gemma-2-27b-it",
+    device_map="auto",
+    torch_dtype=torch.bfloat16)
 
 input_text = "Write me a poem about Machine Learning."
 input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
@@ -148,7 +151,9 @@ from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
 quantization_config = BitsAndBytesConfig(load_in_8bit=True)
 
 tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-27b-it")
-model = AutoModelForCausalLM.from_pretrained("google/gemma-2-27b-it", quantization_config=quantization_config)
+model = AutoModelForCausalLM.from_pretrained(
+    "google/gemma-2-27b-it",
+    quantization_config=quantization_config)
 
 input_text = "Write me a poem about Machine Learning."
 input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
@@ -166,7 +171,9 @@ from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
 quantization_config = BitsAndBytesConfig(load_in_4bit=True)
 
 tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-27b-it")
-model = AutoModelForCausalLM.from_pretrained("google/gemma-2-27b-it", quantization_config=quantization_config)
+model = AutoModelForCausalLM.from_pretrained(
+    "google/gemma-2-27b-it",
+    quantization_config=quantization_config)
 
 input_text = "Write me a poem about Machine Learning."
 input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")