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README.md

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 The HPC-Coder-v2-6.7b model is an HPC code LLM fine-tuned on an instruction dataset catered to common HPC topics such as parallelism, optimization, accelerator porting, etc.
 This version is a fine-tuning of the [Deepseek Coder 6.7b](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base) model. 
 It is fine-tuned on the [hpc-synthetic](https://huggingface.co/datasets/hpcgroup/hpc-synthetic), [oss-instruct](https://huggingface.co/datasets/ise-uiuc/Magicoder-OSS-Instruct-75K), and [evol-instruct](https://huggingface.co/datasets/nickrosh/Evol-Instruct-Code-80k-v1) datasets.
+We utilized the distributed training library [AxoNN](https://github.com/axonn-ai/axonn) to fine-tune in parallel across many GPUs.
 
 HPC-Coder-v2-6.7b is the best performing LLM under 30b parameters on the [ParEval](https://github.com/parallelcodefoundry/ParEval) parallel code generation benchmark in terms of _correctness_ and _performance_.
 It scores similarly to 34B and commercial models like Phind-V2 and GPT-4 on parallel code generation.