reformatted data to jsonl.gz due to utf decode error

data/{test-00000-of-00001.parquet → test.jsonl.gz}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ab49a51e8b4cdbf790ca6b55943a542ad2b5f7bb32bd2119ea02d8f895a89882
-size 11809633
+oid sha256:095362409a8a4e06819ad18d4b59d03604716e9d4e3ac1070cc3019e5146e576
+size 7528112

data/{train-00000-of-00001.parquet → train.jsonl.gz}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c0a67ba42c4cca9f1243e3d2b1250a07c146d1c621b805f684e320d616cfe12e
-size 14342268
+oid sha256:fe4f87ffad31bf6caf3da56a6b671bbc1150e53b839a6e0f9580347334e2488f
+size 9018863

remove_empty/remove_empty.py

@@ -9,9 +9,10 @@ if log_file_path.exists():
     log_file_path.unlink()
 
 tasks = mteb.get_tasks(tasks=["STS22"])
-task = tasks[0]
 
-task.load_data()
+from datasets import load_dataset
+
+dataset = load_dataset(**tasks[0].metadata.dataset)
 
 
 def filter_sample(x):
@@ -24,31 +25,26 @@ def filter_sample(x):
     return False
 
 
-for hf_subset in task.dataset:
-    _ds = task.dataset[hf_subset]
-    for split in _ds:
-        ds = _ds[split]
-        # filter empty sentences
-        n_samples = len(ds)
-        ds = ds.filter(lambda x: filter_sample(x))
-        n_left = len(ds)
-        log = f"Filtered {n_samples - n_left} samples from {n_samples} in {hf_subset} - {split}"
-        with open(log_file_path, "a") as f:
-            f.write(log + "\n")
-        print(log)
-        _ds[split] = ds
-
-    task.dataset[hf_subset] = _ds
-
-save_path = Path(__file__).parent.parent
-
-for hf_subset in task.dataset:
-    _ds = task.dataset[hf_subset]
-    for split in _ds:
-        ds = _ds[split]
-        ds.to_json(save_path / split / (hf_subset + ".jsonl.gz"), compression="gzip")
-        log = f"Saved {hf_subset} - {split} to {save_path / split / (hf_subset + '.jsonl.gz')}"
-
-        with open(log_file_path, "a") as f:
-            f.write(log + "\n")
-        print(log)
+for split in dataset:
+    ds = dataset[split]
+    # filter empty sentences
+    n_samples = len(ds)
+    ds = ds.filter(lambda x: filter_sample(x))
+    n_left = len(ds)
+    log = f"Filtered {n_samples - n_left} samples from {n_samples} in {split}"
+    with open(log_file_path, "a") as f:
+        f.write(log + "\n")
+    print(log)
+
+    dataset[split] = ds
+
+
+save_path = Path(__file__).parent.parent / "data"
+for split in dataset:
+    # dataset[split].to_parquet(save_path / f"{split}-00000-of-00001.parquet")
+    dataset[split].to_json(save_path / f"{split}.jsonl.gz", compression="gzip")
+
+
+
+
+ds = load_dataset(tasks[0].metadata.dataset["path"])