Add MLX verification scripts for DFlash setup

scripts/check_qwen3_coder_next_dflash_only.py

@@ -0,0 +1,18 @@
+#!/usr/bin/env python3
+from dflash.model_mlx import load_draft
+
+
+def main() -> None:
+    draft_id = "z-lab/Qwen3-Coder-Next-DFlash"
+    draft = load_draft(draft_id)
+    cfg = draft.config
+    print("[OK] DFlash draft loaded")
+    print(f"draft_id={draft_id}")
+    print(f"block_size={cfg.block_size}")
+    print(f"num_target_layers={cfg.num_target_layers}")
+    print(f"target_layer_ids={list(cfg.target_layer_ids)}")
+    print("[NOTE] This script does NOT download Qwen/Qwen3-Coder-Next.")
+
+
+if __name__ == "__main__":
+    main()

scripts/test_qwen3_coder_next_mlx.py

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+#!/usr/bin/env python3
+import json
+import traceback
+from huggingface_hub import hf_hub_download
+from dflash.model_mlx import load, load_draft, stream_generate
+
+
+MODEL_ID = "Qwen/Qwen3-Coder-Next"
+DRAFT_ID = "z-lab/Qwen3-Coder-Next-DFlash"
+PROMPT = """You are a coding assistant.
+Write a Python function `is_prime(n: int) -> bool` and include 3 small tests."""
+
+
+def get_total_size_gb(model_id: str) -> float | None:
+    try:
+        idx = hf_hub_download(model_id, "model.safetensors.index.json")
+        with open(idx, "r", encoding="utf-8") as f:
+            data = json.load(f)
+        total_size = data.get("metadata", {}).get("total_size")
+        if total_size is None:
+            return None
+        return total_size / (1024**3)
+    except Exception:
+        return None
+
+
+def main() -> None:
+    print(f"[INFO] target model: {MODEL_ID}")
+    print(f"[INFO] draft model : {DRAFT_ID}")
+    total_size_gb = get_total_size_gb(MODEL_ID)
+    if total_size_gb is not None:
+        print(f"[INFO] target safetensors total size: {total_size_gb:.2f} GiB")
+
+    try:
+        print("[INFO] Loading target model with MLX...")
+        model, tokenizer = load(MODEL_ID)
+        print("[INFO] Loading DFlash draft model...")
+        draft = load_draft(DRAFT_ID)
+        print("[INFO] Starting generation...")
+
+        out_text = []
+        tps = 0.0
+        for r in stream_generate(
+            model=model,
+            draft=draft,
+            tokenizer=tokenizer,
+            prompt=PROMPT,
+            block_size=16,
+            max_tokens=128,
+            temperature=0.2,
+        ):
+            if r.text:
+                print(r.text, end="", flush=True)
+                out_text.append(r.text)
+            tps = r.generation_tps
+            if r.finish_reason is not None:
+                print(f"\n[INFO] finish_reason={r.finish_reason}")
+                break
+
+        print(f"[INFO] generation_tps={tps:.2f} tok/s")
+    except Exception as e:
+        print("\n[ERROR] Generation failed.")
+        print(f"[ERROR] {type(e).__name__}: {e}")
+        print("[ERROR] This often indicates local memory/VRAM is insufficient for this model pair.")
+        traceback.print_exc()
+
+
+if __name__ == "__main__":
+    main()