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Open-weight model · Text generation

ia-vaga1.5B

by Antonio V Toneto17/ia-vaga1.5B

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.

Parameters1.5B
Context32,768
Weights6.2 GB
License
AccessOpen weights
Monthly Downloads

Runs On

What it takes to serve ia-vaga1.5B (1.5B 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 3.1 GB 3.7 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 1.5 GB 1.9 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 0.8 GB 0.9 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 Sep 18, 2026.

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 Antonio V.

Configuration

Architecture
Qwen2ForCausalLM
Context length (tokens)
32,768
Layers
28
Hidden size
1,536
Feed-forward size
8,960
Attention heads
12
Key/value heads
2
Vocabulary size
151,936
Model type
qwen2

Identity and Version

Repository
Toneto17/ia-vaga1.5B
Publisher
Antonio V
Task
Text generation
Modality
Text
Library
transformers
Parameters
1.5B parameters
Languages
Not stated by the source
Revision
6c3e85d7b344a4d2c144e39a8e3620aa12e1ea41
First published
2026-09-18
Last updated
2026-09-18

Files and Weights

9 files, 6.2 GB in total. The weights are 2 files totalling 6.2 GB in gguf, safetensors.

Weights2 files · 6.2 GB
Configuration2 files · 1.6 KB
Tokenizer2 files · 11.4 MB
Documentation1 file · 5.2 KB
Other1 file · 2.5 KB
Repository1 file · 1.6 KB
Every file
FileTypeSizeSHA-256
ia-vaga.ggufWeights3.1 GB ffc5d2a92111
model.safetensorsWeights3.1 GB 2183eb933dc5
config.jsonConfiguration1.4 KB
generation_config.jsonConfiguration242 B
README.mdDocumentation5.2 KB
chat_template.jinjaOther2.5 KB
.gitattributesRepository1.6 KB
tokenizer.jsonTokenizer11.4 MB 3fd169731d2c
tokenizer_config.jsonTokenizer693 B

License and Download

License
Not stated by the source
Access
Open weights, no gate
Download size
6.2 GB
Download from Antonio V

Released by Antonio V through its official repository on Hugging Face.

Built From

Memory Requirements

PrecisionWeights in memory
As published6.2 GB
16-bit3.1 GB
8-bit1.5 GB
4-bit0.8 GB

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

Questions About ia-vaga1.5B

How much GPU memory does ia-vaga1.5B need?

About 3.7 GB at 16-bit and 0.9 GB at 4-bit: the weights (1.5B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run ia-vaga1.5B 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.

What is ia-vaga1.5B's context length?

32,768 tokens, from the maximum position embeddings in its published configuration.

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