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config.json

@@ -1,5 +1,5 @@
 {
-  "model_type": "shivik_m1",
+  "model_type": "shivik_m2",
   "vocab_size": 49152,
   "d_model": 2048,
   "n_layers": 24,
@@ -7,5 +7,8 @@
   "kv_heads": 4,
   "rotary_dim": 128,
   "context_length": 4096,
-  "use_cache": true
+  "use_cache": true,
+  "architectures": [
+    "ShivikM2ForCausalLM"
+  ]
 }

modeling_shivik_m2.py

@@ -189,3 +189,12 @@ class ShivikM2ForCausalLM(PreTrainedModel, GenerationMixin):
         self.model.lm_head.weight = self.model.embed.weight
     def forward(self, input_ids=None, past_key_values=None, **kwargs):
         return self.model(input_ids, past_key_values, use_cache=kwargs.get("use_cache", False))
+
+# === Auto-register with Transformers ===
+try:
+    from transformers.models.auto.configuration_auto import CONFIG_MAPPING
+    from transformers.models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING
+    CONFIG_MAPPING.register("shivik_m2", ShivikM2Config)
+    MODEL_FOR_CAUSAL_LM_MAPPING.register("shivik_m2", ShivikM2ForCausalLM)
+except:
+    pass