from transformers import pipeline

pipe = pipeline("fill-mask")   # or pipeline("fill-mask", model="distilbert/distilroberta-base")

# ────────────────────────────────
# Let the code show you the correct mask token
# ────────────────────────────────
mask_token = pipe.tokenizer.mask_token
print(f"This model expects mask token → {mask_token!r}")
# Usually prints:  This model expects mask token → '<mask>'

# Now build sentence dynamically
sentence = f"The most famous dish in Punjab is {mask_token} roti."

print("\nSentence being sent:", sentence)

results = pipe(sentence, top_k=10)

print("\nTop 10 predictions:")
for i, pred in enumerate(results, 1):
    print(f"{i:2d}. {pred['token_str']:18} {pred['score']:.4f}")