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Open-weight model · Text generation

dolphin-cyber-arabic-merged

by Khaled hamdan Koko12345p/dolphin-cyber-arabic-merged

dolphin-cyber-arabic-merged is an open-weight model for text generation from Khaled hamdan. It has 7.6B parameters and a 32,768-token context. At 16-bit it needs about 18.3 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index. It draws 725 downloads a month.

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.

Parameters7.6B
Context32,768
Weights15.2 GB
License—
AccessOpen weights
Monthly Downloads725

Runs On

What it takes to serve dolphin-cyber-arabic-merged (7.6B 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 15.2 GB 18.3 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 7.6 GB 9.1 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 3.8 GB 4.6 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 7, 2026.

dolphin-cyber-arabic-merged 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 Khaled hamdan.

Configuration

Architecture
Qwen2ForCausalLM
Context length (tokens)
32,768
Layers
28
Hidden size
3,584
Feed-forward size
18,944
Attention heads
28
Key/value heads
4
Vocabulary size
152,064
Model type
qwen2

Identity and Version

Repository
Koko12345p/dolphin-cyber-arabic-merged
Publisher
Khaled hamdan
Task
Text generation
Modality
Text
Library
transformers
Parameters
7.6B parameters
Languages
Not stated by the source
Revision
97473c558f2476063c48134809c20ce13b362829
First published
2026-09-19
Last updated
2026-09-21

Files and Weights

8 files, 15.2 GB in total. The weights are 1 file totalling 15.2 GB in safetensors.

Weights1 file · 15.2 GB
Configuration2 files · 1.7 KB
Tokenizer2 files · 11.4 MB
Documentation1 file · 5.2 KB
Other1 file · 2.6 KB
Repository1 file · 1.6 KB
Every file
FileTypeSizeSHA-256
model.safetensorsWeights15.2 GB e9d69bd97312
config.jsonConfiguration1.4 KB —
generation_config.jsonConfiguration257 B —
README.mdDocumentation5.2 KB —
chat_template.jinjaOther2.6 KB —
.gitattributesRepository1.6 KB —
tokenizer.jsonTokenizer11.4 MB 3fd169731d2c
tokenizer_config.jsonTokenizer724 B —

License and Download

License
Not stated by the source
Access
Open weights, no gate
Download size
15.2 GB
Download from Khaled hamdan

Released by Khaled hamdan through its official repository on Hugging Face.

Built From

Memory Requirements

PrecisionWeights in memory
As published15.2 GB
16-bit15.2 GB
8-bit7.6 GB
4-bit3.8 GB

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

Questions About dolphin-cyber-arabic-merged

How much GPU memory does dolphin-cyber-arabic-merged need?

About 18.3 GB at 16-bit and 4.6 GB at 4-bit: the weights (7.6B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run dolphin-cyber-arabic-merged 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 dolphin-cyber-arabic-merged's context length?

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

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