--- base_model: zai-org/GLM-4.6 tags: - rust - Hyperswitch - LoRA - CPT - Fine-Tuned - Causal-LM pipeline_tag: text-generation language: - en datasets: - AdityaNarayan/HyperSwitch-Repo-CPT-Dataset --- # GLM-4.6-CPT-LoRA-HyperSwitch-v1 A LoRA fine-tuned model based on **zai-org/GLM-4.6** specialized for the [Hyperswitch](https://github.com/juspay/hyperswitch) Rust codebase. This model excels at understanding payment processing patterns, Hyperswitch architecture, and Rust development practices. ## 🎯 Model Description This LoRA adapter was trained on **16,731 samples** extracted from the Hyperswitch codebase to enhance code understanding, explanation, and generation within the payment processing domain. - **Base Model**: zai-org/GLM-4.6 - **Training Type**: Causal Language Modeling (CLM) with LoRA - **Domain**: Payment Processing, Rust Development - **Specialization**: Hyperswitch codebase patterns and architecture ## 📊 Training Details ### LoRA Configuration ```yaml r: 8 # LoRA rank alpha: 16 # LoRA alpha (2*r) dropout: 0.05 # LoRA dropout target_modules: - "q_proj" - "k_proj" - "v_proj" - "o_proj" exclude_modules: - "block_sparse_moe" - "w1" - "w2" - "w3" - "gate" ``` ### Training Hyperparameters - **Epochs**: 3 - **Learning Rate**: 2e-4 (cosine schedule) - **Hardware**: 8 x NVIDIA H200 ## 🛠️ Technical Specifications - **Precision**: bfloat16 - **Inference Speed**: Optimized with Flash Attention 2 ## 🙏 Acknowledgments - **Zai Team** for the excellent GLM 4.6 base model - **Hyperswitch Team** for the open-source payment processing platform - **Hugging Face** for the transformers and PEFT libraries ## 📞 Citation ```bibtex @misc{GLM-4.6-CPT-LoRA-HyperSwitch-v1, title={AdityaNarayan/GLM-4.6-CPT-LoRA-HyperSwitch-v1}, author={Aditya Narayan}, year={2024}, publisher={Hugging Face}, url={https://huggingface.co/AdityaNarayan/GLM-4.6-CPT-LoRA-HyperSwitch-v1} } ```