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3420071 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | #!/usr/bin/env python3
"""Completion CLI: continue a prompt with a trained Notio checkpoint.
Usage:
src/complete.py "Once upon a time" --checkpoint out/notio.pt --n 2
src/complete.py "The little cat" --temp 0.8 --top-k 40 --max-tokens 200
"""
import argparse
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parent))
import sampler
def main():
ap = argparse.ArgumentParser()
ap.add_argument("prompt", nargs="?", default="", help="text to complete (default: story start)")
ap.add_argument("--checkpoint", default="out/notio.pt")
ap.add_argument("--temp", type=float, default=0.9)
ap.add_argument("--top-k", type=int, default=0, help="0 = off")
ap.add_argument("--max-tokens", type=int, default=900)
ap.add_argument("--n", type=int, default=1, help="number of completions")
ap.add_argument("--device", default=None)
a = ap.parse_args()
m, device, ck = sampler.load_model(a.checkpoint, a.device)
print(f"checkpoint: {a.checkpoint} | step {ck['step']} | "
f"train {ck.get('loss', float('nan')):.3f} | val {ck.get('val_loss', float('nan')):.3f} | {device}")
prompt = a.prompt or "Once upon a time"
prompt_ids = sampler.encode_prompt(prompt)
block = m.cfg.layer1.block_size
if len(prompt_ids) >= block:
sys.exit(f"prompt too long: {len(prompt_ids)} ids, block_size {block}")
print(f"prompt: {prompt!r} ({len(prompt_ids)} ids) | temp {a.temp} | top-k {a.top_k}")
for i in range(a.n):
ids = sampler.generate(m, device, prompt_ids, a.max_tokens, a.temp, a.top_k)
print(f"\n=== completion {i} ({len(ids)} ids) ===\n{sampler.ids_to_display(ids)}")
if __name__ == "__main__":
main()
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