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Lyrical_ru2en_Gemma4_SFT_5040_PoetryTranslator-mlx-3Bit
AlekseyCalvin/Lyrical_ru2en_Gemma4_SFT_5040_PoetryTranslator-mlx-3Bit
Lyrical_ru2en_Gemma4_SFT_5040_PoetryTranslator-mlx-3Bit is a image-text-to-text model from AlekseyCalvin. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as apache-2.0.
The Model AlekseyCalvin/Lyricalru2enGemma4SFT5040PoetryTranslator-mlx-3Bit was converted to MLX format from AlekseyCalvin/Lyricalru2enGemma4SFT5040PoetryTranslator using mlx-lm version 0.31.2.
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3.3 GB on disk
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From the Hugging Face model README
AlekseyCalvin/Lyrical_ru2en_Gemma4_SFT_5040_PoetryTranslator-mlx-3Bit
The Model AlekseyCalvin/Lyrical_ru2en_Gemma4_SFT_5040_PoetryTranslator-mlx-3Bit was converted to MLX format from AlekseyCalvin/Lyrical_ru2en_Gemma4_SFT_5040_PoetryTranslator using mlx-lm version 0.31.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("AlekseyCalvin/Lyrical_ru2en_Gemma4_SFT_5040_PoetryTranslator-mlx-3Bit")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
- Task
- Image-Text-to-Text
- Library
- mlx
- Type
- gemma4
- License
- apache-2.0
- Created
- Apr 13, 2026
- Updated
- Apr 13, 2026