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syllagemma-Lyrical_En_ru_meter_parser_3moreEpochs-mlx-6Bit
AlekseyCalvin/syllagemma-Lyrical_En_ru_meter_parser_3moreEpochs-mlx-6Bit
syllagemma-Lyrical_En_ru_meter_parser_3moreEpochs-mlx-6Bit is a machine learning model from AlekseyCalvin. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for mlx.
The Model AlekseyCalvin/syllagemma-LyricalEnrumeterparser3moreEpochs-mlx-6Bit was converted to MLX format from AlekseyCalvin/syllagemma-LyricalEnrumeterparser3moreEpochs using mlx-lm version 0.31.2.
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.safetensors218 MB · 87%
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From the Hugging Face model README
AlekseyCalvin/syllagemma-Lyrical_En_ru_meter_parser_3moreEpochs-mlx-6Bit
The Model AlekseyCalvin/syllagemma-Lyrical_En_ru_meter_parser_3moreEpochs-mlx-6Bit was converted to MLX format from AlekseyCalvin/syllagemma-Lyrical_En_ru_meter_parser_3moreEpochs using mlx-lm version 0.31.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("AlekseyCalvin/syllagemma-Lyrical_En_ru_meter_parser_3moreEpochs-mlx-6Bit")
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)
- Library
- mlx
- Type
- gemma3_text
- Created
- May 16, 2026
- Updated
- May 16, 2026