metadata
base_model: google/gemma-2-9b-it
library_name: transformers
license: gemma
pipeline_tag: text-generation
tags:
- conversational
- mlx
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TheBlueObserver/gemma-2-9b-it-MLX
The Model TheBlueObserver/gemma-2-9b-it-MLX was converted to MLX format from google/gemma-2-9b-it using mlx-lm version 0.20.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("TheBlueObserver/gemma-2-9b-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)