Updated README.md file

README.md

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-# **Model Summary: Mify-Coder-2.5B**
+# **Model Summary: Infy-Coder-2.5B**
 
 ## **Overview**
-Mify-Coder-2.5B-v1 is a breakthrough 2.5B-parameter code model fully designed, engineered, and trained at Infosys on 4.2T tokens on Mify-2.5B base model. Despite its compact size, Mify-Coder-2.5B-v1 sets a new benchmark for small language models, achieving performance parity with frontier open-source models in code generation and tool calling, along with exemplary performance on safety metrics in helpfulness and harmlessness, and superior throughput that surpasses larger frontier models.
+Infy-Coder-2.5B-v1 is a breakthrough 2.5B-parameter code model fully designed, engineered, and trained at Infosys on 4.2T tokens on EnterpriseSLM-2.5B base model. Despite its compact size, Infy-Coder-2.5B-v1 sets a new benchmark for small language models, achieving performance parity with frontier open-source models in code generation and tool calling, along with exemplary performance on safety metrics in helpfulness and harmlessness, and superior throughput that surpasses larger frontier models.
 
 **Developed by**: Infosys Ltd.
 
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 ## **Architecture & Training**
-- **Base Model:** Mify-2.5B  
+- **Base Model:** EnterpriseSLM-2.5B  
 - **Training Phases:**  
   - **Continual Pretraining (CPT):** Next-token prediction with Fill-in-the-Middle (FIM) for structural infilling.  
   - **Supervised Fine-Tuning (SFT):** Instruction alignment for coding tasks, function calling, and safety.  
@@ -46,5 +46,5 @@ Mify-Coder-2.5B-v1 is a breakthrough 2.5B-parameter code model fully designed, e
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 ## **Deployment & Future Work**
-- **Quantization:** The model was optimized for low latency outperforming most sub-8B SLM models. Furthermore, the quantized variants of Mify-Coder can be seamlessly deployed and inferenced on standard desktop environments, eliminating the need for specialized hardware such as GPUs.
-- Future work includes enhancing Mify-Coder with agentic coding competencies and scaling its context length. The model weights will be open-sourced early next year to accelerate research and real-world deployment.
+- **Quantization:** The model was optimized for low latency outperforming most sub-8B SLM models. Furthermore, the quantized variants of Infy-Coder can be seamlessly deployed and inferenced on standard desktop environments, eliminating the need for specialized hardware such as GPUs.
+- Future work includes enhancing Infy-Coder with agentic coding competencies and scaling its context length. The model weights will be open-sourced early next year to accelerate research and real-world deployment.