diff --git a/unsloth/models/llama.py b/unsloth/models/llama.py
index 57f8a42aec..d2251627c5 100644
--- a/unsloth/models/llama.py
+++ b/unsloth/models/llama.py
@@ -358,7 +358,7 @@ def LlamaDecoderLayer_fast_forward(
             (see `past_key_values`).
         past_key_value (`Tuple(torch.FloatTensor)`, *optional*): cached past key and value projection states
     """
-    if past_key_value is not None:
+    if False:#past_key_value is not None:
         do_prefill = not hasattr(self.self_attn, "paged_attention")
 
         # Self Attention
@@ -471,7 +471,7 @@ def LlamaModel_fast_forward(
     pass
 
     # We already handle KV cache position_ids ourselves.
-    if False:#(past_key_values_length != 0):
+    if (past_key_values_length != 0):
         position_ids = torch.arange(
             past_key_values_length, seq_length + past_key_values_length,
             dtype  = torch.int32,
@@ -664,7 +664,7 @@ def LlamaForCausalLM_fast_forward(
     *args, **kwargs,
 ) -> Union[Tuple, CausalLMOutputWithPast]:
 
-    if causal_mask is None and past_key_values is not None:
+    if causal_mask is None and past_key_values is None:
         causal_mask = xformers.attn_bias.LowerTriangularMask()
 
     output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
@@ -767,7 +767,7 @@ class FastLlamaModel:
 
     @staticmethod
     def pre_patch():
-        # LlamaAttention      .forward = LlamaAttention_fast_forward
+        LlamaAttention      .forward = LlamaAttention_fast_forward
         LlamaSdpaAttention  .forward = LlamaAttention_fast_forward
         LlamaFlashAttention2.forward = LlamaAttention_fast_forward
         LlamaDecoderLayer   .forward = LlamaDecoderLayer_fast_forward