metadata
base_model: rinna/gemma-2-baku-2b-it
language:
- ja
- en
license: gemma
tags:
- gemma2
- conversational
- mlx
thumbnail: https://github.com/rinnakk/japanese-pretrained-models/blob/master/rinna.png
base_model_relation: merge
thr3a/gemma-2-baku-2b-it-mlx
The Model thr3a/gemma-2-baku-2b-it-mlx was converted to MLX format from rinna/gemma-2-baku-2b-it using mlx-lm version 0.19.0.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("thr3a/gemma-2-baku-2b-it-mlx")
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)