Image-Text-to-Text
MLX
Safetensors
English
gemma4
heretic
uncensored
decensored
abliterated
ara
conversational
5-bit
Instructions to use zecanard/gemma-4-31b-it-uncensored-heretic-ara-MLX-5bit-int5-affine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use zecanard/gemma-4-31b-it-uncensored-heretic-ara-MLX-5bit-int5-affine with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("zecanard/gemma-4-31b-it-uncensored-heretic-ara-MLX-5bit-int5-affine") config = load_config("zecanard/gemma-4-31b-it-uncensored-heretic-ara-MLX-5bit-int5-affine") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- Pi new
How to use zecanard/gemma-4-31b-it-uncensored-heretic-ara-MLX-5bit-int5-affine with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "zecanard/gemma-4-31b-it-uncensored-heretic-ara-MLX-5bit-int5-affine"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "zecanard/gemma-4-31b-it-uncensored-heretic-ara-MLX-5bit-int5-affine" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use zecanard/gemma-4-31b-it-uncensored-heretic-ara-MLX-5bit-int5-affine with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "zecanard/gemma-4-31b-it-uncensored-heretic-ara-MLX-5bit-int5-affine"
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default zecanard/gemma-4-31b-it-uncensored-heretic-ara-MLX-5bit-int5-affine
Run Hermes
hermes
| base_model: trohrbaugh/gemma-4-31b-it-heretic-ara | |
| language: en | |
| library_name: mlx | |
| license: apache-2.0 | |
| license_link: https://ai.google.dev/gemma/docs/gemma_4_license | |
| pipeline_tag: image-text-to-text | |
| tags: | |
| - mlx | |
| - heretic | |
| - uncensored | |
| - decensored | |
| - abliterated | |
| - ara | |
| # 🦆 zecanard/gemma-4-31b-it-uncensored-heretic-ara-MLX-5bit-int5-affine | |
| [This model](https://huggingface.co/zecanard/gemma-4-31b-it-uncensored-heretic-ara-MLX-5bit-int5-affine) was converted to MLX from [`trohrbaugh/gemma-4-31b-it-heretic-ara`](https://huggingface.co/trohrbaugh/gemma-4-31b-it-heretic-ara) using `mlx-vlm` version **0.5.0**. | |
| Please refer to the [original model card](https://huggingface.co/trohrbaugh/gemma-4-31b-it-heretic-ara) for more details. | |
| ## 🌟 Quality | |
| Quantized vision language model with an effective **7.852 bits per weight**. | |
| `mlx_vlm.convert --quantize --q-group-size 32 --q-bits 5 --q-mode affine` | |
| ## 🛠️ Customizations | |
| This quant is aware of the current date, and also enables thinking (if available). You may disable this behavior by deleting the following line from the chat template, or changing `true` to `false`: | |
| `{%- set enable_thinking = true %}` | |
| You may also need to adjust your environment’s **Reasoning Section Parsing** to recognize `<|channel>thought` as the **Start String**, and `<channel|>` as the **End String**. | |
| ## 🖥️ Use with `mlx` | |
| ```bash | |
| pip install -U mlx-vlm | |
| ``` | |
| ```bash | |
| mlx_vlm.generate --model zecanard/gemma-4-31b-it-uncensored-heretic-ara-MLX-5bit-int5-affine --max-tokens 100 --temperature 0 --prompt "Describe this image." --image <path_to_image> | |
| ``` |