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Open-weight model · Text classification

koelectra-small-v3-discriminator

by Kim MinKyung MinKyungEee/koelectra-small-v3-discriminator

koelectra-small-v3-discriminator is an open-weight model for text classification from Kim MinKyung. 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.

Parameters14M
Context—
Weights—
License—
AccessOpen weights
Monthly Downloads—

Runs On

What it takes to serve koelectra-small-v3-discriminator (14M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

PrecisionWeightsMemory neededCheapest setupPer hourAlso 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.

koelectra-small-v3-discriminator on every accelerator the SAVRN Index prices, at every precision

Model Card

Identity and Version

Repository
MinKyungEee/koelectra-small-v3-discriminator
Publisher
Kim MinKyung
Task
Text classification
Modality
Text
Library
transformers
Parameters
14M parameters
Languages
Not stated by the source
Revision
d17e31e792009735e6ac5684227dff00393afa8e
First published
2026-10-21
Last updated
2026-10-21

License and Download

License
Not stated by the source
Access
Open weights, no gate
Download from Kim MinKyung

Released by Kim MinKyung through its official repository on Hugging Face.

Built From

Memory Requirements

PrecisionWeights in memory
16-bit0.0 GB
8-bit0.0 GB
4-bit0.0 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About koelectra-small-v3-discriminator

How much GPU memory does koelectra-small-v3-discriminator 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-small-v3-discriminator 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

Model · Text classification

koelectra-small-v3-nsmc

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It uses the interface of the SageMaker Inference Toolkit as is, so it can be easily deployed to SageMaker Endpoint.

Open weights mit 14M parameters 512 tokens transformers

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 weights 14M parameters 512 tokens transformers