metadata
base_model: testmoto/gemma-2-llm2024-dpo-02
library_name: transformers
tags:
- mergekit
- merge
- mlx
- mlx
testmoto/gemma-2-9b-mix_coding_magpie
The Model testmoto/gemma-2-9b-mix_coding_magpie was converted to MLX format from testmoto/gemma-2-llm2024-dpo-02 using mlx-lm version 0.20.4.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("testmoto/gemma-2-9b-mix_coding_magpie")
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)