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Model: sabari2005/cyberslm-base
Source: Original Platform

infer_base.py

@@ -0,0 +1,124 @@
+"""
+Base model inference — raw text continuation.
+
+    python Final/infer_base.py --prompt "SQL injection is"
+    python Final/infer_base.py --interactive
+
+The base model is a *continuation* model, not a chat model. Give it the start of
+a sentence and it continues. Asking it a question will not get an answer; it
+will continue the question. Use infer_chat.py for question answering.
+"""
+
+from __future__ import annotations
+
+import argparse
+import sys
+import time
+from pathlib import Path
+
+import torch
+
+_HERE = Path(__file__).resolve().parent
+if str(_HERE) not in sys.path:
+    sys.path.insert(0, str(_HERE))
+
+from cyberslm.model.config import CyberSLMConfig, default_config  # noqa: E402
+from cyberslm.model.model import build_model, count_parameters    # noqa: E402
+
+
+def load(ckpt: Path, device: torch.device):
+    payload = torch.load(ckpt, map_location=device, weights_only=False)
+    if isinstance(payload, dict) and "config" in payload:
+        cfg, state = CyberSLMConfig(**payload["config"]), payload["model_state"]
+    elif isinstance(payload, dict) and "model_state" in payload:
+        cfg, state = default_config(), payload["model_state"]
+    else:
+        cfg, state = default_config(), payload
+    model = build_model(cfg, device=device)
+    model.load_state_dict(state)
+    model.eval()
+    return model, cfg, payload
+
+
+def main() -> int:
+    ap = argparse.ArgumentParser(description="CyberSLM base model (text continuation)")
+    ap.add_argument("--prompt", "-p", default="SQL injection is")
+    ap.add_argument("--interactive", "-i", action="store_true")
+    ap.add_argument("--checkpoint", "-c", default=str(_HERE / "models" / "base.pt"))
+    ap.add_argument("--tokenizer", default=str(_HERE / "tokenizer" / "tokenizer.model"))
+    ap.add_argument("--max-new-tokens", "-m", type=int, default=120)
+    ap.add_argument("--temperature", "-t", type=float, default=0.8,
+                    help="0 = greedy/deterministic")
+    ap.add_argument("--top-k", type=int, default=50)
+    ap.add_argument("--top-p", type=float, default=0.95)
+    ap.add_argument("--repetition-penalty", type=float, default=1.15)
+    ap.add_argument("--device", default=None)
+    ap.add_argument("--model-info", action="store_true")
+    args = ap.parse_args()
+
+    import sentencepiece as spm
+
+    device = torch.device(args.device) if args.device else torch.device(
+        "cuda" if torch.cuda.is_available() else "cpu")
+
+    ckpt = Path(args.checkpoint)
+    if not ckpt.exists():
+        print(f"Checkpoint not found: {ckpt}", file=sys.stderr)
+        return 1
+    sp = spm.SentencePieceProcessor()
+    sp.load(args.tokenizer)
+    model, cfg, payload = load(ckpt, device)
+
+    print(f"model  : {ckpt.name}  ({count_parameters(model)['total']:,} params)")
+    print(f"context: {cfg.max_seq_len}   vocab: {cfg.vocab_size:,}   device: {device}")
+    if isinstance(payload, dict) and payload.get("step"):
+        print(f"trained: step {payload['step']}  val_loss {payload.get('val_loss'):.4f}")
+    if args.model_info:
+        return 0
+
+    def run(text: str) -> None:
+        ids = sp.encode(text, out_type=int)
+        if sp.bos_id() >= 0:
+            ids = [sp.bos_id()] + ids
+        x = torch.tensor([ids], dtype=torch.long, device=device)
+        t0 = time.perf_counter()
+        out = model.generate(
+            x, max_new_tokens=args.max_new_tokens, temperature=args.temperature,
+            top_k=args.top_k, top_p=args.top_p,
+            repetition_penalty=args.repetition_penalty,
+            eos_id=sp.eos_id() if sp.eos_id() >= 0 else None,
+        )
+        dt = time.perf_counter() - t0
+        new = out[0, len(ids):].tolist()
+        if sp.eos_id() in new:
+            new = new[: new.index(sp.eos_id())]
+        print("\n" + "-" * 66)
+        # Decode prompt+continuation TOGETHER. Decoding the continuation
+        # alone and concatenating drops the word-boundary marker on its
+        # first token, gluing the halves ("...is" + "a common" -> "isa").
+        prompt_ids = [t for t in ids if t != sp.bos_id()]
+        print(sp.decode(prompt_ids + new))
+        print("-" * 66)
+        print(f"{len(new)} tokens in {dt:.2f}s ({len(new)/dt if dt else 0:.1f} tok/s)\n")
+
+    if args.interactive:
+        print("\nBase model - type the START of a sentence, it continues it.")
+        print("('exit' to quit)")
+        while True:
+            try:
+                q = input("\n> ").strip()
+            except (EOFError, KeyboardInterrupt):
+                print("\nBye."); break
+            if not q:
+                continue
+            if q.lower() in {"exit", "quit", "q"}:
+                print("Bye."); break
+            run(q)
+        return 0
+
+    run(args.prompt)
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())