Upload 2 files

config.json

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+{
+  "_name_or_path": "my-warning-model",
+  "architectures": ["SimpleModel"],
+  "model_type": "simple-warning-model",
+  "hidden_size": 8
+}

modeling.py

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+# modeling.py
+# Safe demonstration: prints/warns when executed, but DOES NOT fetch or execute remote code.
+
+import warnings
+import sys
+
+# 1) Immediate visible print
+print("\n" + "="*70)
+print("⚠️  WARNING: You are loading a model that declares it MAY execute remote code.")
+print("This repository is a demonstration and DOES NOT execute remote code.")
+print("Before setting `trust_remote_code=True` review the model files manually.")
+print("="*70 + "\n")
+
+# 2) Also raise a Python warning (visible in many environments)
+warnings.warn(
+    "This model includes custom Python code and may execute arbitrary logic when loaded. "
+    "Only load it with trust_remote_code=True after inspecting the repository.",
+    UserWarning,
+)
+
+# 3) Minimal HF-compatible model implementation (harmless).
+from transformers import PreTrainedModel, PretrainedConfig
+
+class SimpleWarningConfig(PretrainedConfig):
+    model_type = "simple-warning-model"
+
+    def __init__(self, hidden_size=8, **kwargs):
+        super().__init__(**kwargs)
+        self.hidden_size = hidden_size
+
+class SimpleModel(PreTrainedModel):
+    config_class = SimpleWarningConfig
+    base_model_prefix = "simple_model"
+
+    def __init__(self, config: SimpleWarningConfig):
+        super().__init__(config)
+        # keep internals minimal and harmless
+        try:
+            import torch.nn as nn
+            self.dummy = nn.Linear(config.hidden_size, config.hidden_size)
+        except Exception:
+            # if torch not available, we still want the module importable
+            self.dummy = None
+
+    def forward(self, *args, **kwargs):
+        # harmless placeholder forward
+        try:
+            import torch
+            if self.dummy is None:
+                return torch.zeros(1, self.config.hidden_size)
+            return self.dummy(torch.zeros(1, self.config.hidden_size))
+        except Exception:
+            # if torch is missing, return a plain Python fallback
+            return [[0.0] * self.config.hidden_size]