Update README.md

README.md

@@ -22,9 +22,9 @@ datasets:
 - nvidia/OpenMathInstruct-2
 ---
 
-# SmallCoder V2 (303M)
+# SmallCoder (303M)
 
-SmallCoder V2 is a **303 Million parameter** Large Language Model (LLM) trained from scratch, specializing in code generation and algorithmic reasoning.
+SmallCoder is a **303 Million parameter** Large Language Model (LLM) trained from scratch, specializing in code generation and algorithmic reasoning.
 
 This checkpoint is the result of a 6 Billion token Supervised Fine-Tuning (SFT) run, which **fixed a critical End-of-Sequence (EOS) token bug** present in previous versions.
 
@@ -34,17 +34,17 @@ This model demonstrates state-of-the-art (SOTA) coding performance for its size,
 
 ## 🚀 Key Performance (Benchmarks)
 
-The goal of SmallCoder V2 was to maximize coding performance in a compact (<500M) package. This model achieves SOTA scores that rival or exceed models in the 1B+ class.
+The goal of SmallCoder was to maximize coding performance in a compact (<500M) package. This model achieves SOTA scores that rival or exceed models in the 1B+ class.
 
 | Model | Size | HumanEval (pass@1) | MBPP (pass@1) |
 | :--- | :---: | :---: | :---: |
-| **SmallCoder V2 (S4.1)** | **303M** | **27.4%** | **31.0%** |
+| **SmallCoder (S4.1)** | **303M** | **27.4%** | **31.0%** |
 | TinyLlama-1.1B | 1.1B | ~26.4% | ~27.6% |
 | MPT-1B-Instruct | 1.0B | ~22.0% | ~25.0% |
 | Zephyr-1.3B SFT | 1.3B | 31.0% | 34.0% |
 | Mistral-7B Base | 7B | 30.5% | 47.5% |
 
-SmallCoder V2 (303M) nearly achieves **parity with Mistral 7B** on HumanEval while being **23x smaller**.
+SmallCoder (303M) nearly achieves **parity with Mistral 7B** on HumanEval while being **23x smaller**.
 
 ## 🧠 Model Architecture