| base_model: google/gemma-2-27b-it | |
| library_name: transformers | |
| license: gemma | |
| pipeline_tag: text-generation | |
| tags: | |
| - 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 | |
| # mlx-community/gemma-2-27b-it-8-bit | |
| The Model [mlx-community/gemma-2-27b-it-8-bit](https://huggingface.co./mlx-community/gemma-2-27b-it-8-bit) was converted to MLX format from [google/gemma-2-27b-it](https://huggingface.co./google/gemma-2-27b-it) using mlx-lm version **0.19.1**. | |
| ## Use with mlx | |
| ```bash | |
| pip install mlx-lm | |
| ``` | |
| ```python | |
| from mlx_lm import load, generate | |
| model, tokenizer = load("mlx-community/gemma-2-27b-it-8-bit") | |
| 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) | |
| ``` | |