AshtonIsNotHere/CodeLlama_7B_nlp_pp
AshtonIsNotHere/CodeLlama_7B_nlp_pp is a 7 billion parameter causal language model, fine-tuned from CodeLlama-7b-hf. This model is specifically optimized for code completion tasks within the NLP++ programming language. It was trained on a specialized dataset of NLP++ code, achieving an accuracy of 0.8968 on its evaluation set. Its primary strength lies in assisting developers with NLP++ code generation.
Loading preview...
Model Overview
AshtonIsNotHere/CodeLlama_7B_nlp_pp is a 7 billion parameter language model derived from the codellama/CodeLlama-7b-hf architecture. This model has undergone specialized fine-tuning to excel in code completion for the NLP++ programming language.
Key Capabilities
- NLP++ Code Completion: Specifically trained on a dataset comprising scraped NLP++ code and examples from the VisualText website.
- Performance: Achieved a validation accuracy of 0.8968 with a loss of 0.4129 during training.
- Training Details: Trained using a multi-node, multi-GPU setup with DeepSpeed Z3, utilizing a learning rate of 0.00012 over 7 epochs.
Intended Use Cases
This model is particularly well-suited for developers working with NLP++ code, offering assistance in:
- Accelerating NLP++ development: By providing accurate and contextually relevant code suggestions.
- Improving code quality: Through intelligent completion that adheres to NLP++ syntax and common patterns.
Limitations
As the model is fine-tuned exclusively on NLP++ code, its performance on other programming languages or general natural language tasks may be limited. Further information regarding broader limitations is pending.