Large Language Model for automobile
Preprint |
10.55415/deep-2024-0004.v1
This is not the most recent version. There is anewer
versionof this content available.
Abstract
The expansion in scale has significantly raised hardware requirements, making it exceedingly challenging to deploy models on mobile devices such as smartphones and tablets.
To deploy on cars , we trained a 7-billion-parameter automobile model, which outperforms GPT-3.5 in the automotive domain.
Surpassing all models in areas such as automotive maintenance, navigation queries, and beyond.
To deploy on cars , we trained a 7-billion-parameter automobile model, which outperforms GPT-3.5 in the automotive domain.
Surpassing all models in areas such as automotive maintenance, navigation queries, and beyond.
Keywords
Subject Area
Version History
- 01 May 2024 18:30 Version 1
Scores
0
Rapid Rating Times:
0
· Level of
Quality: -
· Level of Repeatability: -
· Level of Innovation: -
· Level of Impact: -
Rapid Rating Times:
0
· Level of
Quality: -· Level of Repeatability: -
· Level of Innovation: -
· Level of Impact: -
*Each rating ranges from 0-5
Rapid Rating
Your professional field is different from the direction of this article.
Go Settings!
Not yet Peer Reviewed
The content is available
under CC BY-NC-ND 4.0
License CreativeCommons.org
The author(s) have declared they have no conflict of interest with regard to
this content
