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Create prep_datasets.py
Browse files- prep_datasets.py +58 -0
prep_datasets.py
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# prep_datasets.py
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# One-time exporter: saves PIQA + HellaSwag to clean JSONL for offline use.
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from datasets import load_dataset
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import json, os
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OUT_DIR = "data"
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os.makedirs(OUT_DIR, exist_ok=True)
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def write_jsonl(path, rows):
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with open(path, "w", encoding="utf-8") as f:
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for r in rows:
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f.write(json.dumps(r, ensure_ascii=False) + "\n")
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# --- PIQA ---
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print("Downloading PIQA…")
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piqa = load_dataset("piqa")
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def piqa_clean(split):
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out = []
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for ex in split:
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out.append({
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"goal": ex.get("goal") or "",
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"sol1": ex.get("sol1") or "",
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"sol2": ex.get("sol2") or "",
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"label": int(ex.get("label", 0))
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})
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return out
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piqa_train = piqa["train"]
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piqa_valid = piqa["validation"]
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print("Writing PIQA JSONL…")
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write_jsonl(os.path.join(OUT_DIR, "piqa_train.jsonl"), piqa_clean(piqa_train))
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write_jsonl(os.path.join(OUT_DIR, "piqa_valid.jsonl"), piqa_clean(piqa_valid))
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# --- HellaSwag ---
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print("Downloading HellaSwag…")
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hs = load_dataset("hellaswag")
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def hs_clean(split):
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out = []
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for ex in split:
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out.append({
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# keep both ctx and ctx_a to be safe (some variants use both)
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"ctx": ex.get("ctx") or "",
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"ctx_a": ex.get("ctx_a") or "",
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"endings": list(ex.get("endings") or []),
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"label": int(ex.get("label", 0))
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})
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return out
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hs_train = hs["train"]
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hs_valid = hs["validation"]
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print("Writing HellaSwag JSONL…")
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write_jsonl(os.path.join(OUT_DIR, "hellaswag_train.jsonl"), hs_clean(hs_train))
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write_jsonl(os.path.join(OUT_DIR, "hellaswag_valid.jsonl"), hs_clean(hs_valid))
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print("Done. Files created in ./data")
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