Create create_dataset.py

create_dataset.py

@@ -0,0 +1,38 @@
+from datasets import load_dataset
+import hashlib
+
+def main():
+    ds = load_dataset("GAIR/lima" ,split="train")
+    ds_test = load_dataset("GAIR/lima" ,split="test")
+    
+    ds = ds.map(lambda x: {
+        "length": len(x['conversations'])
+        })
+    
+    ds = ds.filter(lambda x: x['length'] == 2)
+    
+    ds = ds.map(
+        lambda x: {
+        "prompt_id": hashlib.sha256(x['conversations'][0].encode("utf-8")).hexdigest(),
+        "prompt": x['conversations'][0],
+        "messages": [
+            {"role": "user", "content": x['conversations'][0]},
+            {"role": "assistant", "content": x['conversations'][1]}
+        ],
+        "meta": {"source": "lima", "category": x['source']}
+    })
+    
+    ds_test = ds_test.map(lambda x: {
+        "prompt_id": hashlib.sha256(x['conversations'][0].encode("utf-8")).hexdigest(),
+        "prompt": x['conversations'][0],
+        "messages": [
+            {"role": "user", "content": x['conversations'][0]},
+        ],
+        "meta": {"source": "lima", "category": x['source']}
+    })
+    
+    ds.push_to_hub("HuggingFaceH4/lima", split = "train_ift")
+    ds_test.push_to_hub("HuggingFaceH4/lima", split = "test_ift")
+
+if __name__ == "__main__":
+    main()