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README.md

@@ -53,13 +53,21 @@ model = PeftModel.from_pretrained(
 
 # Generate outputs
 
+datasets = []
+with open("./elyza-tasks-100-TV_0.jsonl", "r") as f:
+    item = ""
+    for line in f:
+      line = line.strip()
+      item += line
+      if item.endswith("}"):
+        datasets.append(json.loads(item))
+        item = ""
+
 PROMPT = """### 指示
 {input}
 ### 回答
 """
 
-datasets = ...
-
 results = []
 FastLanguageModel.for_inference(model)
 for data in tqdm(datasets):
@@ -78,6 +86,11 @@ for data in tqdm(datasets):
         )[0]
     output = tokenizer.decode(outputs[tokenized_input.size(1):], skip_special_tokens=True)
     results.append({"task_id": data["task_id"], "input": input, "output": output})
+
+with open(f"./outputs.jsonl", 'w', encoding='utf-8') as f:
+    for result in results:
+        json.dump(result, f, ensure_ascii=False)
+        f.write('\n')
 ```