Delete modeling_jnu_tsb.py

modeling_jnu_tsb.py

@@ -1,43 +0,0 @@
-from __future__ import annotations
-
-from typing import Any, Dict, Optional
-
-import torch
-from torch import nn
-from transformers import PreTrainedModel
-
-try:
-    from .configuration_jnu_tsb import JNUTSBConfig
-except ImportError:  # pragma: no cover - local execution fallback
-    from configuration_jnu_tsb import JNUTSBConfig
-
-
-class JNUTSBModel(PreTrainedModel):
-    """Tiny placeholder model for Hugging Face AutoModel loading.
-
-    The actual forecasting and routing logic lives in ``runtime.JNUTSBRuntime``.
-    This class exists so that ``AutoModel.from_pretrained(..., trust_remote_code=True)``
-    can load a normal model object from the Hub.
-    """
-
-    config_class = JNUTSBConfig
-    base_model_prefix = "jnu_tsb"
-    main_input_name = "inputs"
-
-    def __init__(self, config: JNUTSBConfig) -> None:
-        super().__init__(config)
-        self.dummy = nn.Parameter(torch.zeros(1), requires_grad=False)
-
-    def forward(self, *args: Any, **kwargs: Any) -> Dict[str, str]:
-        return {
-            "message": "JNU-TSB is a router wrapper. Use pipeline(task='jnu-tsb', ...) or model.predict(...)."
-        }
-
-    def predict(self, inputs: Optional[Dict[str, Any]] = None, **kwargs: Any) -> Any:
-        try:
-            from .runtime import JNUTSBRuntime
-        except ImportError:  # pragma: no cover
-            from runtime import JNUTSBRuntime
-
-        runtime = JNUTSBRuntime.from_config(self.config)
-        return runtime.predict(inputs=inputs, **kwargs)