metadata
license: apache-2.0
library_name: mlx
tags:
- language
- granite-4.0
- mlx
base_model:
- ethicalabs/granite-4.0-1b-MLX
- ethicalabs/kurtis-e1-granite-4.0-1b-adapter-MLX
pipeline_tag: text-generation
datasets:
- ethicalabs/Kurtis-E1-SFT
- ethicalabs/kurtis-v2-sft-mix-tiny
base_model_relation: merge
ethicalabs/kurtis-e1-granite-4.0-1b-MLX
This model ethicalabs/kurtis-e1-granite-4.0-1b-MLX was converted to MLX format from ethicalabs/granite-4.0-1b-MLX using mlx-lm version 0.28.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("ethicalabs/kurtis-e1-granite-4.0-1b-MLX")
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)