Downloads · 30 days
129
24% of all-time downloads
mlx-community/translategemma-27b-it-6bit
translategemma-27b-it-6bit is a translation model from mlx-community. Use it when you need text moved from one language to another. It is set up for mlx. The card lists the license as gemma.
This model mlx-community/translategemma-27b-it-6bit was converted to MLX format from google/translategemma-27b-it (via mlx-community/translategemma-27b-it-bf16)
Downloads · 30 days
129
24% of all-time downloads
All-time downloads
531
Public
Parameters
27B
22 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors21.9 GB · 100%
How the weights are stored.
U3227B · 100%
From the Hugging Face model README
This model mlx-community/translategemma-27b-it-6bit was converted to MLX format from google/translategemma-27b-it (via mlx-community/translategemma-27b-it-bf16) using mlx-lm version 0.30.4.
6-bit (6.50 bits per weight, 22.0 GB) targets 32 GB unified-memory Macs: the 8-bit conversion needs more memory than a 32 GB machine can dedicate to inference, while 6-bit affine quantization stays close to 8-bit output quality. For smaller machines see the 4-bit conversion.
TranslateGemma 27B is Google's translation-specialized Gemma 3 model supporting 55 languages. It uses a structured translation message rendered through the model's chat template.
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/translategemma-27b-it-6bit")
messages = [{
"role": "user",
"content": [{
"type": "text",
"source_lang_code": "en",
"target_lang_code": "pl",
"text": "The city council approved the new bike path along the river.",
}],
}]
prompt = tokenizer.apply_chat_template(messages, add_generation_prompt=True)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms.