metadata
license: gemma
library_name: transformers
tags:
- conversational
- mlx
base_model: AXCXEPT/EZO-Humanities-9B-gemma-2-it
pipeline_tag: text-generation
thr3a/EZO-Humanities-9B-gemma-2-it-mlx
The Model thr3a/EZO-Humanities-9B-gemma-2-it-mlx was converted to MLX format from AXCXEPT/EZO-Humanities-9B-gemma-2-it using mlx-lm version 0.18.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("thr3a/EZO-Humanities-9B-gemma-2-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)