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Open-weight model

ml-classification

by Pari R Kaur Bonsaipari06/ml-classification

ml-classification is an open-weight model from Pari R Kaur, released under BSD 3-Clause License. It has 24,832 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.

Parameters24,832
Context—
Weights—
Licensebsd-3-clause
AccessOpen weights
Monthly Downloads—

Runs On

What it takes to serve ml-classification (24,832 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 23, 2026.

ml-classification on every accelerator the SAVRN Index prices, at every precision

Model Card

Identity and Version

Repository
Bonsaipari06/ml-classification
Publisher
Pari R Kaur
Task
Not stated by the source
Modality
Other
Library
Not stated by the source
Parameters
24,832 parameters
Languages
Not stated by the source
Revision
0fec20888bfd14a5efc3ffcd07c3c82ea7fc5e76
First published
2026-10-20
Last updated
2026-10-20

License and Download

License
bsd-3-clause
Access
Open weights, no gate
Download from Pari R Kaur

Released by Pari R Kaur through its official repository on Hugging Face. Read the license.

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 ml-classification

How much GPU memory does ml-classification need?

About 0 GB at 16-bit and 0 GB at 4-bit: the weights (24,832 parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run ml-classification 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.

Can I use ml-classification commercially?

Yes. ml-classification is released under BSD 3-Clause License. The BSD 3-Clause License is permissive. It permits commercial use and redistribution with the copyright notice, and forbids using the authors' names to endorse derived products without permission.