Upload HF wrapper

modeling_kimik2.py

@@ -0,0 +1,29 @@
+"""
+Minimal HuggingFace wrapper for KimiK2 model recognition
+"""
+import torch
+from transformers import PreTrainedModel, PretrainedConfig
+from transformers.modeling_outputs import CausalLMOutputWithPast
+
+
+class KimiK2Config(PretrainedConfig):
+    model_type = "kimi-k2"
+    
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+
+class KimiK2ForCausalLM(PreTrainedModel):
+    config_class = KimiK2Config
+    
+    def __init__(self, config):
+        super().__init__(config)
+        # This is just for HF recognition - actual loading happens via direct PyTorch
+        print("Note: Use the direct PyTorch loading method shown in the README for this model.")
+    
+    def forward(self, input_ids, **kwargs):
+        # Placeholder for HF compatibility
+        batch_size, seq_len = input_ids.shape
+        vocab_size = getattr(self.config, 'vocab_size', 50304)
+        logits = torch.randn(batch_size, seq_len, vocab_size)
+        return CausalLMOutputWithPast(logits=logits)