remove swefracas and add swemnli

data/swemnli/swemnli_dev.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7a09e1ccebab854a33b9d182193e456fe4ecf69fe24f791e173ba621823fc85f
+size 2362732

data/swemnli/swemnli_test.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:232a35144b8c6a13b71e08be5622faeb8c955b43a7dc9572784f9ea66464061a
+size 54611

data/swemnli/swemnli_train.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d701f7d8e1e214cddb10399db415e00454994662e135a32bf6aaa96dadf4e3e1
+size 96150107

superlim-2.py

@@ -65,7 +65,7 @@ _SweFaq_DESCRIPTION = """\
 Vanliga frågor från svenska myndigheters webbsidor med svar i randomiserad ordning"""
 _SweFaq_CITATION = """\
 """
-_SweFracas_DESCRIPTION = """\
+_SweMNLI_DESCRIPTION = """\
 A textual inference/entailment problem set, derived from FraCas. The original English Fracas [1] was converted to html and edited by Bill MacCartney [2], 
 and then automatically translated to Swedish by Peter Ljunglöf and Magdalena Siverbo [3]. The current tabular form of the set was created by Aleksandrs Berdicevskis 
 by merging the Swedish and English versions and removing some of the problems. Finally, Lars Borin went through all the translations, correcting and Swedifying them manually. 
@@ -123,9 +123,9 @@ _TASKS = {
     "swefaq": "swefaq",
     "swepar": "sweparaphrase",
     "swesat": "swesat-synonyms",
+    "swemnli": "swemnli",
     "swewic": "swewic",
     "swedn": "swedn",
-    "swefracas": "swefracas",
     "swediagnostics": "swediagnostics"
 }
 
@@ -176,7 +176,7 @@ class SuperLim(datasets.GeneratorBasedBuilder):
         datasets.BuilderConfig(name="swedn", version=VERSION, description=_SweDN_DESCRIPTION),
         datasets.BuilderConfig(name="swewic", version=VERSION, description=_SweWic_DESCRIPTION),
         datasets.BuilderConfig(name="argumentation_sent", version=VERSION, description=_argumentation_sentences_DESCRIPTION),
-        datasets.BuilderConfig(name="swefracas", version=VERSION, description=_SweFracas_DESCRIPTION),
+        datasets.BuilderConfig(name="swemnli", version=VERSION, description=_SweMNLI_DESCRIPTION),
         datasets.BuilderConfig(name="swediagnostics", version=VERSION, description=_SweDiag_DESCRIPTION)
     ]
 
@@ -272,13 +272,13 @@ class SuperLim(datasets.GeneratorBasedBuilder):
                     "sentence": datasets.Value("string")
                 }
             )
-        elif self.config.name == 'swefracas':
+        elif self.config.name == 'swemnli':
             features = datasets.Features(
                 {
                     "id": datasets.Value("string"),
-                    "original_id": datasets.Value("string"),
-                    "attribute": datasets.Value("string"),
-                    "value": datasets.Value("string")
+                    "premise": datasets.Value("string"),
+                    "hypothesis": datasets.Value("string"),
+                    "label": datasets.Value("string")
                 }
             )
         elif self.config.name == 'swediagnostics':
@@ -335,7 +335,7 @@ class SuperLim(datasets.GeneratorBasedBuilder):
             },
         )
         splits.append(split_test)
-        if self.config.name in ("absabank-imm", "dalaj-ged", "swefaq", "swewic", "swedn", "swepar"):
+        if self.config.name in ("absabank-imm", "dalaj-ged", "swefaq", "swewic", "swemnli", "swedn", "swepar"):
             data_dir_dev = dl_manager.download_and_extract(os.path.join(_URL,DATA_FOLDER,f"{_TASKS[self.config.name]}_dev.{file_format}"))
             split_dev = datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
@@ -345,7 +345,7 @@ class SuperLim(datasets.GeneratorBasedBuilder):
                 },
             )
             splits.append(split_dev)
-        if self.config.name in ("absabank-imm", "dalaj-ged", "swefaq", "swewic", "argumentation_sent", "swedn", "swepar"):
+        if self.config.name in ("absabank-imm", "dalaj-ged", "swefaq", "swewic", "swemnli", "argumentation_sent", "swedn", "swepar"):
             data_dir_train = dl_manager.download_and_extract(os.path.join(_URL,DATA_FOLDER,f"{_TASKS[self.config.name]}_train.{file_format}"))
             split_train = datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
@@ -464,11 +464,12 @@ class SuperLim(datasets.GeneratorBasedBuilder):
                     'label': row['label']
                 }
 
-            elif self.config.name == "swefracas":
+            elif self.config.name == "swemnli":
                 yield key, {
-                    'original_id': row['original_id'],
-                    'attribute': row['attribute'],
-                    'value': row['value']
+                    'id': row['id'],
+                    'premise': row['premise'],
+                    'hypothesis': row['hypothesis'],
+                    'label': row['label']
                 }
 
             elif self.config.name == "swedn":