metadata

license: gemma
library_name: transformers
pipeline_tag: text-generation
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base_model: google/gemma-2-9b
tags:
  - mlx

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)