This is the model card of a transformers model that has been pushed on the Hub. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. Use the code below to get started with the model. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
Open-weight model · Text classification
koelectra-base-v3-discriminator-news-classifier
by Sea yyeeoon031/koelectra-base-v3-discriminator-news-classifier
koelectra-base-v3-discriminator-news-classifier is an open-weight model for text classification from Sea. It has 14M parameters. At 16-bit it needs about 0 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.
Runs On
What it takes to serve koelectra-base-v3-discriminator-news-classifier (14M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.
| Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits |
|---|---|---|---|---|---|
| 16-bit | 0.0 GB | 0.0 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 0.0 GB | 0.0 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 0.0 GB | 0.0 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Oct 22, 2026.
Model Card
Identity and Version
- Repository
- yyeeoon031/koelectra-base-v3-discriminator-news-classifier
- Publisher
- Sea
- Task
- Text classification
- Modality
- Text
- Library
- transformers
- Parameters
- 14M parameters
- Languages
- Not stated by the source
- Revision
- 7917107b54ae4ffac2aa56fe6c984e4caf4acb0e
- First published
- 2026-10-21
- Last updated
- 2026-10-21
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
Released by Sea through its official repository on Hugging Face.
Built From
- Described by arXiv:1910.09700
Memory Requirements
| Precision | Weights in memory |
|---|---|
| 16-bit | 0.0 GB |
| 8-bit | 0.0 GB |
| 4-bit | 0.0 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About koelectra-base-v3-discriminator-news-classifier
How much GPU memory does koelectra-base-v3-discriminator-news-classifier need?
About 0 GB at 16-bit and 0 GB at 4-bit: the weights (14M parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run koelectra-base-v3-discriminator-news-classifier on?
At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Similar Models