From 69044ce605587d1f1dd008dcfbdee5b15967c47f Mon Sep 17 00:00:00 2001
From: Daniel Han <danielhanchen@gmail.com>
Date: Mon, 3 Mar 2025 23:32:02 -0800
Subject: [PATCH] Update llama.py

---
 unsloth/models/llama.py | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/unsloth/models/llama.py b/unsloth/models/llama.py
index 475f82a5b1..b5bfa3cbfa 100644
--- a/unsloth/models/llama.py
+++ b/unsloth/models/llama.py
@@ -1684,10 +1684,10 @@ class FastLlamaModel:
 
         statistics = \
            f"==((====))==  Unsloth {__version__}: Fast {model_patcher.__name__[4:-5]} patching. Transformers: {transformers_version}.\n"\
-           f"   {chr(92)}{chr(92)}   /|    GPU: {gpu_stats.name}. Max memory: {max_memory} GB. Platform: {platform_system}.\n"\
+           f"   {chr(92)}{chr(92)}   /|    {gpu_stats.name}. Num GPUs = {torch.cuda.device_count()}. Max memory: {max_memory} GB. Platform: {platform_system}.\n"\
            f"O^O/ {chr(92)}_/ {chr(92)}    Torch: {torch.__version__}. CUDA: {gpu_stats.major}.{gpu_stats.minor}. CUDA Toolkit: {torch.version.cuda}. Triton: {triton_version}\n"\
            f"{chr(92)}        /    Bfloat16 = {str(SUPPORTS_BFLOAT16).upper()}. FA [Xformers = {xformers_version}. FA2 = {HAS_FLASH_ATTENTION}]\n"\
-           f' "-____-"     Free Apache license: http://github.com/unslothai/unsloth'
+           f' "-____-"     Free license: http://github.com/unslothai/unsloth'
         print(statistics)
 
         # Warn about fast transfers
@@ -1879,11 +1879,11 @@ class FastLlamaModel:
         # Cannot use \\ since it will cause a SyntaxWarning in Python 3.12
         # Instead use chr(92) == \\
         debug_info = """debug_info = \\
-        f"==((====))==  Unsloth - 2x faster free finetuning | Num GPUs = {args.world_size}\\n"\\
-        f"   {chr(92)}{chr(92)}   /|    Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,}\\n"\\
-        f"O^O/ {chr(92)}_/ {chr(92)}    Batch size per device = {self._train_batch_size:,} | Gradient Accumulation steps = {args.gradient_accumulation_steps}\\n"\\
-        f"{chr(92)}        /    Total batch size = {total_train_batch_size:,} | Total steps = {max_steps:,}\\n"\\
-        f' "-____-"     Number of trainable parameters = {get_model_param_count(model, trainable_only=True):,}'
+        f"==((====))==  Unsloth - 2x faster free finetuning | Num GPUs used = {len(set(p.device for p in model.parameters()))}\\n"\\
+        f"   {chr(92)}{chr(92)}   /|    Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,} | Total steps = {max_steps:,}\\n"\\
+        f"O^O/ {chr(92)}_/ {chr(92)}    Batch size per device = {self._train_batch_size:,} | Gradient accumulation steps = {args.gradient_accumulation_steps}\\n"\\
+        f"{chr(92)}        /    Data Parallel GPUs = {args.world_size} | Total batch size = {total_train_batch_size:,}\\n"\\
+        f' "-____-"     Number of trainable parameters = {get_model_param_count(model, trainable_only=True):,}/{get_model_param_count(model)}'
         logger.warning(debug_info)
         import subprocess, re, gc
         for _ in range(3):