metadata
pipeline_tag: text-generation
inference: false
license: apache-2.0
library_name: transformers
tags:
- language
- granite-3.2
- mlx
base_model: ibm-granite/granite-3.2-8b-instruct-preview
mlx-community/granite-3.2-8b-instruct-preview-8bit
The Model mlx-community/granite-3.2-8b-instruct-preview-8bit was converted to MLX format from ibm-granite/granite-3.2-8b-instruct-preview using mlx-lm version 0.21.0.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/granite-3.2-8b-instruct-preview-8bit")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)