feat(project_structure): 重构项目目录并添加运行脚本

supervised_finetuning/sft_chinese_instruct.py

@@ -0,0 +1,41 @@
+from datasets import DatasetDict
+from datasets import load_dataset, concatenate_datasets
+from utils import process_dataset
+
+
+def replace_seg(query:str, response:str) -> str:
+    replacements = {
+        "\\[": "$$", "\\]": "$$",
+        "\\(": "$", "\\)": "$"
+    }
+    for old, new in replacements.items():
+        query = query.replace(old, new)
+        response = response.replace(old, new)
+
+    return query, response
+
+def process_func(input_dict: dict):
+    query = input_dict["prompt"] if input_dict["prompt"] else ""
+    resp = input_dict["response"] if input_dict["response"] else ""
+    query, resp = replace_seg(query, resp)
+    
+    return {"query": query, "response": resp }
+
+
+if __name__ == "__main__":
+    all_data = ['stem_zh', 'infinity-instruct', 'firefly', 'magpie', 'dpsk-r1-distil', 
+                'coig-cqia', 'disc-law', 'neo_sft_phase2', 'chinese-medical', 'chinese-reasoning-distil', 
+                'psycho-10k-dpsk-r1', 'sof-c-zh', 'industryinstruction', 'Chinese-QA-AFAF']
+    
+    datasets = []
+    for subset in all_data:
+        ds = load_dataset("Mxode/Chinese-Instruct", name=subset)
+        datasets.append(ds["train"]) 
+    
+    combined_dataset = concatenate_datasets(datasets)
+    
+    process_dataset(
+        dataset_dict=DatasetDict({"train": combined_dataset}),
+        output_subdir="chinese-instruct",
+        process_func=process_func,
+    )