metadata
pipeline_tag: text-generation
inference: false
license: apache-2.0
library_name: transformers
tags:
- language
- granite-3.2
- mlx
- mlx-my-repo
base_model: ibm-granite/granite-3.2-2b-instruct
zshannon/granite-3.2-2b-instruct-Q4-mlx
The Model zshannon/granite-3.2-2b-instruct-Q4-mlx was converted to MLX format from ibm-granite/granite-3.2-2b-instruct using mlx-lm version 0.21.5.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("zshannon/granite-3.2-2b-instruct-Q4-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)