testmoto/gemma-2-9b-synthetic_coding
The Model testmoto/gemma-2-9b-synthetic_coding was converted to MLX format from google/gemma-2-9b using mlx-lm version 0.20.1.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("testmoto/gemma-2-9b-synthetic_coding")
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)