Upload folder using huggingface_hub

longbench_pro.py

@@ -0,0 +1,40 @@
+from datasets import Dataset, DatasetDict, GeneratorBasedBuilder, Split, SplitGenerator, Value, Features, load_dataset
+
+class LongBenchPro(GeneratorBasedBuilder):
+    VERSION = "1.0.0"
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description="LongBench Pro dataset",
+            features=Features({
+                "id": Value("string"),
+                "context": Value("string"),
+                "language": Value("string", choices=["English", "Chinese"]),
+                "token_length": Value("string", choices=["8k", "16k", "32k", "64k", "128k", "256k"]),
+                "primary_task": Value("string"),
+                "secondary_task": Value("string"),
+                "contextual_requirement": Value("string", choices=["Full", "Partial"]),
+                "question_nonthinking": Value("string"),
+                "question_thinking": Value("string"),
+                "answer": Value("list"),
+                "difficulty": Value("string", choices=["Easy", "Moderate", "Hard", "Extreme"]),
+            }),
+            supervised_keys=None,
+            homepage="https://huggingface.co/datasets/caskcsg/LongBench_Pro",
+        )
+
+    def _split_generators(self, dl_manager):
+        data_path = dl_manager.download_and_extract("longbench_pro.json")
+        return [
+            SplitGenerator(
+                name=Split.TRAIN,
+                gen_kwargs={"filepath": data_path}
+            )
+        ]
+
+    def _generate_examples(self, filepath):
+        import json
+        with open(filepath, encoding="utf-8") as f:
+            data = json.load(f)
+            for i, item in enumerate(data):
+                yield i, item