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Open-weight model · Feature extraction

tiny-audio-granite-qwen-frozen-2

by Alex Kroman mazesmazes/tiny-audio-granite-qwen-frozen-2

tiny-audio-granite-qwen-frozen-2 is an open-weight model for feature extraction from Alex Kroman. It has 13M 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.

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.

Parameters13M
Context—
Weights319.5 MB
License—
AccessOpen weights
Monthly Downloads—

Runs On

What it takes to serve tiny-audio-granite-qwen-frozen-2 (13M 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 12, 2026.

tiny-audio-granite-qwen-frozen-2 on every accelerator the SAVRN Index prices, at every precision

Model Card

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).

Excerpt from the card by Alex Kroman.

Configuration

Architecture
ASRModel
Vocabulary size
248,192
Model type
asr_model

Identity and Version

Repository
mazesmazes/tiny-audio-granite-qwen-frozen-2
Publisher
Alex Kroman
Task
Feature extraction
Modality
Text
Library
transformers
Parameters
13M parameters
Languages
Not stated by the source
Revision
2aeae2c4f287d10c06ae3d4477a7122d04d2ca96
First published
2026-09-23
Last updated
2026-09-24

Files and Weights

19 files, 339.8 MB in total. The weights are 3 files totalling 319.5 MB in bin, safetensors.

Weights3 files · 319.5 MB
Configuration11 files · 220.9 KB
Tokenizer2 files · 20.0 MB
Documentation1 file · 5.2 KB
Other1 file · 7.8 KB
Repository1 file · 1.6 KB
Every file
FileTypeSizeSHA-256
adapter_model.safetensorsWeights269.2 MB 3b86a5046179
model.safetensorsWeights50.4 MB 893eae509b0d
training_args.binWeights5.3 KB dfa197f5c599
adapter_config.jsonConfiguration1.3 KB —
alignment.pyConfiguration9.4 KB —
asr_config.pyConfiguration21.0 KB —
asr_modeling.pyConfiguration120.2 KB —
asr_pipeline.pyConfiguration17.5 KB —
asr_processing.pyConfiguration9.0 KB —
config.jsonConfiguration8.8 KB —
diarization.pyConfiguration25.4 KB —
generation_config.jsonConfiguration231 B —
preprocessor_config.jsonConfiguration457 B —
projectors.pyConfiguration7.6 KB —
README.mdDocumentation5.2 KB —
chat_template.jinjaOther7.8 KB —
.gitattributesRepository1.6 KB —
tokenizer.jsonTokenizer20.0 MB a454aca253aa
tokenizer_config.jsonTokenizer1.2 KB —

License and Download

License
Not stated by the source
Access
Open weights, no gate
Download size
319.5 MB
Download from Alex Kroman

Released by Alex Kroman through its official repository on Hugging Face.

Built From

Memory Requirements

PrecisionWeights in memory
As published319.5 MB
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 tiny-audio-granite-qwen-frozen-2

How much GPU memory does tiny-audio-granite-qwen-frozen-2 need?

About 0 GB at 16-bit and 0 GB at 4-bit: the weights (13M parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run tiny-audio-granite-qwen-frozen-2 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.

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