metadata
library_name: transformers
license: apache-2.0
license_link: https://ai.google.dev/gemma/docs/gemma_4_license
pipeline_tag: any-to-any
tags:
- heretic
- uncensored
- decensored
- abliterated
- ara
- mlx
- mlx-my-repo
base_model: coder3101/gemma-4-E4B-it-heretic
cookietimeh/gemma-4-E4B-it-heretic-mlx-8Bit
The Model cookietimeh/gemma-4-E4B-it-heretic-mlx-8Bit was converted to MLX format from coder3101/gemma-4-E4B-it-heretic using mlx-lm version 0.31.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("cookietimeh/gemma-4-E4B-it-heretic-mlx-8Bit")
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)