[–] Aldopareja 2y ago ↗ One of the authors here. This is the paper backing up the technology.https://arxiv.org/abs/2403.01081
[–] thebeardisred 2y ago ↗ IMHO the `README.md` for instructlab itself does a terrible job of explaining the value of the software. I found the taxonomy `README.md` much more helpful: https://github.com/instructlab/taxonomy/blob/main/README.md [–] [deleted] 2y ago ↗ (comment deleted) [–] jeremyeder 2y ago ↗ Hi Brian, thanks for that feedback; we are definitely going to improve our documentation and will take this into account. I hope you're able to test out InstructLab and let us know how it goes. [–] cashsri 2y ago ↗ Here's a couple of explainers on LAB/InstructLab that may help https://research.ibm.com/blog/LLM-generated-data https://developers.redhat.com/articles/2024/05/07/instructla...
[–] jeremyeder 2y ago ↗ Hi Brian, thanks for that feedback; we are definitely going to improve our documentation and will take this into account. I hope you're able to test out InstructLab and let us know how it goes.
[–] cashsri 2y ago ↗ Here's a couple of explainers on LAB/InstructLab that may help https://research.ibm.com/blog/LLM-generated-data https://developers.redhat.com/articles/2024/05/07/instructla...
[–] tarasglek 2y ago ↗ This seems like a really nice framework for feeding documentation into llms.Would be curious to use same dataset without fine-tuned llm for RAG over same data.Then one could immediately make use of building the dataset and then measure gains from training.
6 comments
[ 9.3 ms ] story [ 505 ms ] threadhttps://arxiv.org/abs/2403.01081
Would be curious to use same dataset without fine-tuned llm for RAG over same data.
Then one could immediately make use of building the dataset and then measure gains from training.