Update README.md

README.md

@@ -37,7 +37,6 @@ This llama model was trained 2x faster with [Unsloth](https://github.com/unsloth
 ### 2. モデル・トークナイザの読み込み
 
 ```python
-
 from transformers import (
     AutoModelForCausalLM,
     AutoTokenizer,
@@ -74,7 +73,6 @@ tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True, to
 ### 3. 入力データの準備
 
 ```python
-
 # Load dataset
 datasets = []
 with open("./elyza-tasks-100-TV_0.jsonl", "r") as f:
@@ -85,13 +83,11 @@ with open("./elyza-tasks-100-TV_0.jsonl", "r") as f:
       if item.endswith("}"):
         datasets.append(json.loads(item))
         item = ""
-
 ```
 
 ### 4. 推論実行
 
 ```python
-
 results = []
 for data in tqdm(datasets):
 
@@ -118,14 +114,11 @@ for data in tqdm(datasets):
 ### 5. 出力の保存
 
 ```python
-
 import re
 model_name = re.sub(".*/", "", model_name)
 with open(f"./{model_name}-outputs.jsonl", 'w', encoding='utf-8') as f:
     for result in results:
         json.dump(result, f, ensure_ascii=False)  # ensure_ascii=False for handling non-ASCII characters
         f.write('\n')
-
-
 ```
 ## ・以上の手順で、{model_name}-outputs.jsonlというファイルに推論結果が書き出されます。