diff --git a/unsloth/models/llama.py b/unsloth/models/llama.py
index 3c4d8f3b38..c4488127d9 100644
--- a/unsloth/models/llama.py
+++ b/unsloth/models/llama.py
@@ -390,7 +390,7 @@ def LlamaAttention_fast_forward(
     past_key_value = (K, V) if use_cache else None
 
     # Attention module
-    if (not HAS_FLASH_ATTENTION and attention_mask is None):
+    if False:#(not HAS_FLASH_ATTENTION and attention_mask is None):
         # Xformers memory efficient attention
         # Also has Flash Attention v2 dispatching
         Q = Q.transpose(1, 2)
@@ -427,10 +427,10 @@ def LlamaAttention_fast_forward(
         pass
         # Must be contiguous or else results are False!
         # https://github.com/pytorch/pytorch/issues/112577
-        Q, K, V = Q.contiguous(), K.contiguous(), V.contiguous()
+        # Q, K, V = Q.contiguous(), K.contiguous(), V.contiguous()
         # Needs (batch_size, n_heads, seq_len, head_dim)
         # is_casual and attention_mask must not be both set!
-        A = scaled_dot_product_attention(Q, K, V, attn_mask = attention_mask, is_causal = False)
+        A = scaled_dot_product_attention(Q, K, V, is_causal = True)
         # Go back to (batch_size, seq_len, n_heads, head_dim)
         A = A.transpose(1, 2).contiguous()
     pass
@@ -1028,7 +1028,6 @@ def CausalLM_fast_forward(fast_forward_inference):
 pass
 
 
-@torch._disable_dynamo
 def PeftModelForCausalLM_fast_forward(
     self,
     input_ids=None,