karmakorma/sasbuddylm-v3-merged
karmakorma/sasbuddylm-v3-merged is a 7.6 billion parameter clinical-SAS-programming-specialized large language model, fine-tuned from Qwen2.5-Coder-7B-Instruct. This merged base+LoRA model is designed to generate SAS programs from TOON-formatted clinical specifications. It achieves a score of 0.82 on ClinicalCodeBench for L0-L5 SAS execution across 53 cases, making it highly effective for specialized clinical programming tasks.
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Overview
karmakorma/sasbuddylm-v3-merged is a 7.6 billion parameter language model specifically fine-tuned for clinical SAS programming. It is based on the Qwen2.5-Coder-7B-Instruct architecture, combining the base model with LoRA adaptations for specialized performance. This model is provided as a merged version, ready for direct deployment.
Key Capabilities
- Clinical SAS Program Generation: Excels at generating SAS programs based on TOON-formatted clinical specifications.
- Performance: Achieves a score of 0.82 on the ClinicalCodeBench, evaluated across 53 cases for L0-L5 SAS execution.
- Deployment Ready: The merged base+LoRA model is suitable for direct deployment, with recommendations for using the Text Generation Inference (TGI) container on Hugging Face Inference Endpoints.
- Hardware Efficiency: Designed to run efficiently, fitting within 24 GB of VRAM in bfloat16 precision (e.g., on an L4 GPU).
- Chat Template: Utilizes the standard Qwen2.5 ChatML format, with the template provided in the tokenizer.
Intended Use Cases
- Automating the creation of SAS programs from clinical specifications.
- Assisting clinical programmers in generating code for data analysis and reporting.
Technical Details
- Model Type: Fine-tuned from Qwen2.5-Coder-7B-Instruct.
- Parameter Count: 7.6 billion.
- Context Length: 32768 tokens.
- Recommended
torch_dtype:bfloat16.