library_name: transformers license: apache-2.0 license_link: https://ai.google.dev/gemma/docs/gemma_4_license pipeline_tag: image-text-to-text base_model: llmfan46/gemma-4-Ortenzya-The-Creative-Wordsmith-31B-it-uncensored-heretic tags:

text-generation-inference
transformers
unsloth
gemma4
heretic
uncensored
decensored
abliterated
ara
creative writing
translation
visual novels
finetune
roleplay
rp
mlx
mlx-my-repo language:
en
jpn

cookietimeh/gemma-4-Ortenzya-The-Creative-Wordsmith-31B-it-uncensored-heretic-mlx-8Bit

The Model cookietimeh/gemma-4-Ortenzya-The-Creative-Wordsmith-31B-it-uncensored-heretic-mlx-8Bit was converted to MLX format from llmfan46/gemma-4-Ortenzya-The-Creative-Wordsmith-31B-it-uncensored-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-Ortenzya-The-Creative-Wordsmith-31B-it-uncensored-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)

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate model, tokenizer = load("cookietimeh/gemma-4-Ortenzya-The-Creative-Wordsmith-31B-it-uncensored-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)