Runs On My 16GB Mac
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Model Architecture and Objective
Puchify T1 integrates the S.A.F.E framework as a parallel evaluation system that operates during inference. The architecture employs specialized attention mechanisms for safety assessment while maintaining standard autoregressive generation capabilities.
This model PuchifyT1-4B-dwq6-mlx was converted to MLX format from Puchify/PuchifyT1-4B using mlx-lm version 0.26.0.
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("PuchifyT1-4B-dwq6-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)