Geert / README.md
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metadata
base_model: mlx-community/gemma-2-9b-it-4bit
library_name: transformers
license: gemma
pipeline_tag: text-generation
tags:
  - conversational
  - mlx
  - mlx
extra_gated_heading: Access Gemma on Hugging Face
extra_gated_prompt: >-
  To access Gemma on Hugging Face, you’re required to review and agree to
  Google’s usage license. To do this, please ensure you’re logged in to Hugging
  Face and click below. Requests are processed immediately.
extra_gated_button_content: Acknowledge license

TeunS/Geert

The Model TeunS/Geert was converted to MLX format from mlx-community/gemma-2-9b-it-4bit using mlx-lm version 0.19.3.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("TeunS/Geert")

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)