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 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+databases/academic.sqlite filter=lfs diff=lfs merge=lfs -text
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+databases/bike_1.sqlite filter=lfs diff=lfs merge=lfs -text
+databases/chinook_1.sqlite filter=lfs diff=lfs merge=lfs -text
+databases/college_2.sqlite filter=lfs diff=lfs merge=lfs -text
+databases/cre_Drama_Workshop_Groups.sqlite filter=lfs diff=lfs merge=lfs -text
+databases/csu_1.sqlite filter=lfs diff=lfs merge=lfs -text
+databases/flight_4.sqlite filter=lfs diff=lfs merge=lfs -text
+databases/formula_1.sqlite filter=lfs diff=lfs merge=lfs -text
+databases/imdb.sqlite filter=lfs diff=lfs merge=lfs -text
+databases/sakila_1.sqlite filter=lfs diff=lfs merge=lfs -text
+databases/soccer_1.sqlite filter=lfs diff=lfs merge=lfs -text
+databases/store_1.sqlite filter=lfs diff=lfs merge=lfs -text
+databases/world_1.sqlite filter=lfs diff=lfs merge=lfs -text
+databases/wta_1.sqlite filter=lfs diff=lfs merge=lfs -text

README.md

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+# Processed MultiSpider Dataset
+
+This is a processed version of the MultiSpider dataset with the following enhancements:
+- Combined questions from multiple languages (en, de, es, fr, ja, vi, zh)
+- Added complexity levels for each SQL query (easy, medium, hard)
+- Split into balanced train and test sets
+
+## Dataset Statistics
+- Train set: 4248 examples
+- Test set: 1064 examples
+- Languages: English, German, Spanish, French, Japanese, Vietnamese, Chinese
+- Database files: 166 SQLite files
+
+## Format
+
+Each example follows this structure:
+```json
+{
+  "db_id": "database_name",
+  "query": "SELECT * FROM table WHERE condition",
+  "complexity_level": "easy|medium|hard",
+  "questions": {
+    "en": "English natural language question",
+    "de": "German natural language question",
+    "es": "Spanish natural language question",
+    "fr": "French natural language question",
+    "ja": "Japanese natural language question",
+    "vi": "Vietnamese natural language question",
+    "zh": "Chinese natural language question"
+  }
+}
+```
+
+## Usage
+
+This dataset is ideal for:
+1. Supervised Fine-Tuning (SFT) of text-to-SQL models
+2. Curriculum learning (using complexity levels)
+3. Cross-lingual training and evaluation
+4. Guided Reinforcement Learning from Policy Optimization (GRPO)

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