metadata

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

testmoto/gemma-2-9b-jglue_jssts

The Model testmoto/gemma-2-9b-jglue_jssts was converted to MLX format from google/gemma-2-9b using mlx-lm version 0.20.2.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("testmoto/gemma-2-9b-jglue_jssts")

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)