Update README.md

README.md

@@ -37,18 +37,22 @@ Ruby Code Generator is a versatile tool crafted to streamline the interaction be
 ## Training procedure
 
 **1. Load Dataset and Model:**
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     - Load the bigcode/the-stack-smol dataset using the Hugging Face Datasets library.
     - Filter for the specified subset (data/ruby) and split (train).
     - Load the bigcode/starcoder2-3b model from the Hugging Face Hub with '4-bit' quantization.
     
 **2. Data Preprocessing:**
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     - Tokenize the code text using the appropriate tokenizer for the chosen model.
     - Apply necessary cleaning or normalization (e.g., removing comments, handling indentation).
     - Create input examples suitable for the model's architecture (e.g., with masked language modeling objectives).
     
 **3. Configure Training:**
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     - Initialize a Trainer object (likely from a library like Transformers).
     - Set training arguments based on the provided args:
+    
       - Learning rate, optimizer, scheduler
       - Gradient accumulation steps
       - Weight decay