license: apache-2.0
base_model: prithivMLmods/gemma-4-E2B-it-Uncensored-MAX
language:

• en
  pipeline_tag: any-to-any
  library_name: transformers
  tags:
• text-generation-inference
• uncensored
• abliterated
• unfiltered
• unredacted
• refusal-ablated
• vllm
• pytorch
• bf16
• max
• alignment-modified
• reasoning
• agent
• mlx
• mlx-my-repo
  datasets:
• prithivMLmods/harm_bench

fengpeisheng1/gemma-4-E2B-it-Uncensored-MAX-mlx-4Bit

The Model fengpeisheng1/gemma-4-E2B-it-Uncensored-MAX-mlx-4Bit was converted to MLX format from prithivMLmods/gemma-4-E2B-it-Uncensored-MAX using mlx-lm version 0.31.2.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("fengpeisheng1/gemma-4-E2B-it-Uncensored-MAX-mlx-4Bit")

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)