apache
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2 changed files with 2 additions and 2 deletions
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@ -984,7 +984,7 @@ class FastLlamaModel:
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front_spaces = re.match('([\s\t]{1,})', inner_training_loop).group(0)
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debug_info = """debug_info = \\
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f"==((====))== Unsloth - Free Apache OSS license | Num GPUs = {args.world_size}\\n"\\
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f"==((====))== Unsloth - 2x faster free finetuning | Num GPUs = {args.world_size}\\n"\\
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f" \\\\\\ /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,}\\n"\\
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f"O^O/ \\_/ \\ Batch size per device = {self._train_batch_size:,} | Gradient Accumulation steps = {args.gradient_accumulation_steps}\\n"\\
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f"\\ / Total batch size = {total_train_batch_size:,} | Total steps = {max_steps:,}\\n"\\
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@ -389,7 +389,7 @@ class FastMistralModel(FastLlamaModel):
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front_spaces = re.match('([\s\t]{1,})', inner_training_loop).group(0)
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debug_info = """debug_info = \\
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f"==((====))== Unsloth - Free Apache OSS license | Num GPUs = {args.world_size}\\n"\\
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f"==((====))== Unsloth - 2x faster free finetuning | Num GPUs = {args.world_size}\\n"\\
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f" \\\\\\ /| Num examples = {num_examples:,} | Num Epochs = {num_train_epochs:,}\\n"\\
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f"O^O/ \\_/ \\ Batch size per device = {self._train_batch_size:,} | Gradient Accumulation steps = {args.gradient_accumulation_steps}\\n"\\
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f"\\ / Total batch size = {total_train_batch_size:,} | Total steps = {max_steps:,}\\n"\\
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