Fixes tie weights.

modeling_indictrans.py

@@ -1643,7 +1643,7 @@ class IndicTransModel(IndicTransPreTrainedModel):
 # Copied from transformers.models.m2m_100.modeling_m2m_100.M2M100ForConditionalGeneration->IndicTrans
 class IndicTransForConditionalGeneration(IndicTransPreTrainedModel, GenerationMixin):
     base_model_prefix = "model"
-    _tied_weights_keys = None
+    _tied_weights_keys = ["decoder.embed_tokens.weight", "lm_head.weight"]
     _label_smoothing = 0.0
 
     def __init__(self, config: IndicTransConfig):
@@ -1653,19 +1653,20 @@ class IndicTransForConditionalGeneration(IndicTransPreTrainedModel, GenerationMi
             config.decoder_embed_dim, config.decoder_vocab_size, bias=False
         )
 
-        if config.share_decoder_input_output_embed:
-            self.lm_head.weight = self.model.decoder.embed_tokens.weight
-
         self.post_init()
 
-    def tie_weights(self):
-        pass
+    def tie_weights(self):
+       if self.config.share_decoder_input_output_embed:
+           self._tie_or_clone_weights(self.decoder.embed_tokens, self.lm_head)
 
     def get_encoder(self):
-        return self.model.get_encoder()
+        return self.model.encoder
 
     def get_decoder(self):
-        return self.model.get_decoder()
+        return self.model.decoder
+
+    def get_input_embeddings(self):
+        return self.model.encoder.embed_tokens
 
     def get_output_embeddings(self):
         return self.lm_head