renamed targets to labels in bharatAI's forward method

model.py

@@ -116,7 +116,7 @@ class BharatAI(PreTrainedModel):
         elif isinstance(module, nn.Embedding):
             torch.nn.init.normal_(module.weight, mean=0.0, std=0.02)
 
-    def forward(self, input_ids, index, targets=None):
+    def forward(self, input_ids, index, labels=None): #, targets
         B, T = index.shape
         x = input_ids
 
@@ -128,13 +128,13 @@ class BharatAI(PreTrainedModel):
         x = self.ln_f(x) # (B,T,C)
         logits = self.lm_head(x) # (B,T,vocab_size)
 
-        if targets is None:
+        if labels is None:
             loss = None
         else:
             B, T, C = logits.shape
             logits = logits.view(B*T, C)
-            targets = targets.view(B*T)
-            loss = F.cross_entropy(logits, targets)
+            labels = labels.view(B*T)
+            loss = F.cross_entropy(logits, labels)
 
         return logits, loss