daniellnichols commited on
Commit
5de9bdd
1 Parent(s): 33d2e15

fix dataset name in readme

Browse files
Files changed (1) hide show
  1. README.md +1 -1
README.md CHANGED
@@ -11,7 +11,7 @@ tags:
11
 
12
  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.
13
  This version is a fine-tuning of the [Deepseek Coder 6.7b](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base) model.
14
- 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.
15
  We utilized the distributed training library [AxoNN](https://github.com/axonn-ai/axonn) to fine-tune in parallel across many GPUs.
16
 
17
  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_.
 
11
 
12
  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.
13
  This version is a fine-tuning of the [Deepseek Coder 6.7b](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base) model.
14
+ It is fine-tuned on the [hpc-instruct](https://huggingface.co/datasets/hpcgroup/hpc-instruct), [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.
15
  We utilized the distributed training library [AxoNN](https://github.com/axonn-ai/axonn) to fine-tune in parallel across many GPUs.
16
 
17
  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_.