From e2aa4d6a1a11086ac5641bfa2d9afdd41f312902 Mon Sep 17 00:00:00 2001
From: Daniel Han <danielhanchen@gmail.com>
Date: Thu, 31 Oct 2024 12:38:20 -0700
Subject: [PATCH] Revert "Tied weights"

This reverts commit 820cd4efef5d173f2200ef184b3d8856ba09d75b.
---
 unsloth/models/llama.py | 6 +-----
 1 file changed, 1 insertion(+), 5 deletions(-)

diff --git a/unsloth/models/llama.py b/unsloth/models/llama.py
index 0e9b70a8b2..c0175bbfaf 100644
--- a/unsloth/models/llama.py
+++ b/unsloth/models/llama.py
@@ -1838,8 +1838,7 @@ class FastLlamaModel:
         except: old_output_embedding = torch.zeros(0)
 
         # Check for tied weights as well
-        # is_tied = old_input_embedding.data_ptr() == old_output_embedding.data_ptr()
-        is_tied = model.config.tie_word_embeddings
+        is_tied = old_input_embedding.data_ptr() == old_output_embedding.data_ptr()
 
         # Check pad token's id -> we need to expand the embedding
         if len(tokenizer) > old_input_embedding.shape[0]:
@@ -1888,9 +1887,6 @@ class FastLlamaModel:
         else:
             correct_dtype = old_input_embedding.dtype
         pass
-
-        # Finally tie them if needed!
-        if is_tied: model.tie_weights()
         
         # Also patch all dtypes - BnB seems to not allocate the correct type?
         # BnB default dtype seems to be float16!