Update README.md

README.md

@@ -29,7 +29,7 @@ A fine-tuned version of [microsoft/graphcodebert-base](https://huggingface.co/mi
 
 This model extends GraphCodeBERT's pre-training with continued MLM training on C++ and Erlang code. GraphCodeBERT incorporates data flow graphs (DFGs) alongside token sequences, enabling the model to capture semantic relationships between variables in addition to syntactic structure. The fine-tuning objective combines standard MLM loss with an edge-prediction loss over the DFG.
 
-- **Developed by:** [GitHub link to be added]
+- **Developed by:** https://github.com/MatthewsO3/GraphCode-CErl-base
 - **Model type:** Transformer encoder (RoBERTa-based), Masked Language Model
 - **Languages:** C++, Erlang (training); Python, Java, JavaScript (zero-shot evaluation)
 - **License:** MIT
@@ -37,7 +37,7 @@ This model extends GraphCodeBERT's pre-training with continued MLM training on C
 
 ### Model Sources
 
-- **Repository:** [To be added]
+- **Repository:** https://github.com/MatthewsO3/GraphCode-CErl-base
 
 ## Uses
 
@@ -234,4 +234,4 @@ If you use this model, please also cite the original GraphCodeBERT paper:
 
 ## Model Card Contact
 
-[To be added — link your GitHub or HuggingFace profile here]
+https://github.com/MatthewsO3