Modelpublic

mlx-community/YanoljaNEXT-Rosetta-12B-2510-mlx-bf16

sourceHugging Facegemmaupdated 10mo agoView on Hugging Face

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Model Card

mlx-community/YanoljaNEXT-Rosetta-12B-2510-mlx-bf16

This model mlx-community/YanoljaNEXT-Rosetta-12B-2510-mlx-bf16 was converted to MLX format from yanolja/YanoljaNEXT-Rosetta-12B-2510 using mlx-lm version 0.28.1.

You can find more similar translation-related MLX model quants for an Apple Mac Studio at https://huggingface.co/bibproj

Model Description

This model is a 12-billion parameter, decoder-only language model built on the Gemma3 architecture and fine-tuned by Yanolja NEXT. It is specifically designed to translate structured data (JSON format) while preserving the original data structure.

The model was trained on a multilingual dataset covering the following languages equally:

—Arabic
—Bulgarian
—Chinese
—Czech
—Danish
—Dutch
—English
—Finnish
—French
—German
—Greek
—Gujarati
—Hebrew
—Hindi
—Hungarian
—Indonesian
—Italian
—Japanese
—Korean
—Persian
—Polish
—Portuguese
—Romanian
—Russian
—Slovak
—Spanish
—Swedish
—Tagalog
—Thai
—Turkish
—Ukrainian
—Vietnamese

While optimized for these languages, it may also perform effectively on other languages supported by the base Gemma3 model.

Use with mlx

bash

pip install mlx-lm

python

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/YanoljaNEXT-Rosetta-12B-2510-mlx-bf16")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)