EraX-Translator-V1.0-i1-GGUF Open-Source Translation Model - Supports Multiple Languages and Works Well in Low-Resource Environments

Erax Translator V1.0 I1 GGUF

Developed by mradermacher

Quantized version of EraX-Translator-V1.0, supporting multilingual translation, especially suitable for low-resource environments and translations involving Classical Chinese and Buddhist scriptures.

Machine Translation Supports Multiple Languages#Multilingual translation #Low-resource optimization #Buddhist scripture translation

Downloads 659

Release Time : 4/14/2025

Model Overview

This is a multilingual translation model supporting languages including Vietnamese, English, Russian, French, Chinese, Cantonese, German, Japanese, Korean, Hindi, and Ukrainian. The model has been quantized for low-resource environments.

Model Features

Multilingual support

Supports translation between 11 languages, including major languages and dialects like Cantonese.

Low-resource optimization

Quantized for efficient operation in resource-constrained environments.

Specialized domain support

Particularly suitable for Classical Chinese and Buddhist scripture translations.

Multiple quantization options

Offers various quantization levels from extreme compression to high quality to meet different needs.

Model Capabilities

Text translation

Multilingual translation

Classical Chinese translation

Buddhist scripture translation

Use Cases

Academic research

Ancient text translation

Translating Classical Chinese literature into modern languages or other foreign languages

Buddhist scripture studies

Assisting researchers in understanding Buddhist classics across different languages

Commercial applications

Multilingual content localization

Providing translation services for multinational corporations

🚀 EraX-Translator-V1.0

A multilingual translation model supporting multiple languages, offering various quantized versions for different usage scenarios.

🚀 Quick Start

The model is based on the transformers library and supports multiple languages including Vietnamese, English, Russian, French, etc. You can refer to the following sections for detailed information.

✨ Features

Multilingual Support: Supports translation between multiple languages, including Vietnamese, English, Russian, French, Chinese, Cantonese, German, Japanese, Korean, Hindi, and Ukrainian.
Multiple Quantized Versions: Offers a variety of quantized versions with different sizes and qualities, suitable for different resource requirements.
Low - Resource Adaptability: Suitable for low - resource scenarios, such as ancient Chinese and Buddhist texts translation.

📦 Installation

No specific installation steps are provided in the original document.

💻 Usage Examples

No code examples are provided in the original document.

📚 Documentation

About

The model is a weighted/imatrix quants of https://huggingface.co/erax-ai/EraX-Translator-V1.0. Static quants are available at https://huggingface.co/mradermacher/EraX-Translator-V1.0-GGUF.

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi - part files.

Provided Quants

(sorted by size, not necessarily quality. IQ - quants are often preferable over similar sized non - IQ quants)

Link	Type	Size/GB	Notes
GGUF	i1 - IQ1_S	1.2	for the desperate
GGUF	i1 - IQ1_M	1.3	mostly desperate
GGUF	i1 - IQ2_XXS	1.4
GGUF	i1 - IQ2_XS	1.5
GGUF	i1 - IQ2_S	1.5
GGUF	i1 - IQ2_M	1.6
GGUF	i1 - Q2_K_S	1.7	very low quality
GGUF	i1 - IQ3_XXS	1.8	lower quality
GGUF	i1 - Q2_K	1.8	IQ3_XXS probably better
GGUF	i1 - IQ3_XS	2.0
GGUF	i1 - IQ3_S	2.0	beats Q3_K*
GGUF	i1 - Q3_K_S	2.0	IQ3_XS probably better
GGUF	i1 - IQ3_M	2.1
GGUF	i1 - Q3_K_M	2.2	IQ3_S probably better
GGUF	i1 - Q3_K_L	2.3	IQ3_M probably better
GGUF	i1 - IQ4_XS	2.4
GGUF	i1 - IQ4_NL	2.5	prefer IQ4_XS
GGUF	i1 - Q4_0	2.5	fast, low quality
GGUF	i1 - Q4_K_S	2.5	optimal size/speed/quality
GGUF	i1 - Q4_K_M	2.6	fast, recommended
GGUF	i1 - Q4_1	2.7
GGUF	i1 - Q5_K_S	2.9
GGUF	i1 - Q5_K_M	2.9
GGUF	i1 - Q6_K	3.3	practically like static Q6_K

Here is a handy graph by ikawrakow comparing some lower - quality quant types (lower is better):

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

🔧 Technical Details

No technical details are provided in the original document.

📄 License

The license of this model is gemma.

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