Nanbeige-4.3-33B-Heretic-Uncensored · MLX 8-bit

Built by VeriSafe.Live: we build, fine-tune, quantize and serve open-weights models.
An uncensored 33B model, running natively on your Mac.

What we offer

Service	What you get
🎯 Custom fine-tuning	Any open-weights model adapted to your data, domain and tone.
🧪 Training from scratch	Models designed and trained end to end for companies and research institutes.
⚡ Quantization	Compact builds, like this MLX release, that run on the hardware you already have.
🌐 Hosted API access	Our models served for you, ready to call.
🔓 Uncensored models	Open-weights models with refusals removed, for unrestricted work.

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Why this model

Uncensored: built on Luni/Nanbeige-4.3-33B-Heretic, an abliterated Nanbeige 4.3 33B with reduced refusals.
Mac-native: MLX format for Apple Silicon unified memory, about 32.8 GiB on disk.
Long context: keeps the base model's 262K-token context window.
Drop-in serving: works with mlx_lm.generate, mlx_lm.chat and the OpenAI-compatible mlx_lm.server.
Open license: Apache-2.0, inherited from the base model.

Technical details


Base model	Luni/Nanbeige-4.3-33B-Heretic, abliterated from Nanbeige/Nanbeige4.3-33B
Architecture	LlamaForCausalLM, ~33B parameters, 52 layers, hidden size 7168, 56 heads / 8 KV heads
Quantization	MLX affine, 8 bits, group size 64 (~8.5 bits per weight); non-quantized tensors in bfloat16
Size on disk	~32.8 GiB
License	Apache-2.0

⚠️ Refusal behaviour has been reduced via abliteration, so the model may produce content the original would decline. Use responsibly.

Quickstart

pip install -U mlx-lm
mlx_lm.generate --model junafinity/Nanbeige-4.3-33B-Heretic-Uncensored-MLX-8bit --prompt "Write a fast binary search in Python." --max-tokens 512

from mlx_lm import load, generate

model, tokenizer = load("junafinity/Nanbeige-4.3-33B-Heretic-Uncensored-MLX-8bit")
messages = [{"role": "user", "content": "Write a fast binary search in Python."}]
prompt = tokenizer.apply_chat_template(messages, add_generation_prompt=True)
print(generate(model, tokenizer, prompt=prompt, max_tokens=512, verbose=True))

OpenAI-compatible server:

mlx_lm.server --model junafinity/Nanbeige-4.3-33B-Heretic-Uncensored-MLX-8bit --port 8080

💬 Need a custom model?

If your company or research institute would like us to fine-tune any open-weights model, or train one from scratch, we'd be happy to help.

📧 info@verisafe.live

_{License and attribution. Released under Apache-2.0. Based on Luni/Nanbeige-4.3-33B-Heretic, derived from Nanbeige/Nanbeige4.3-33B. The base model's original card is included as README_ORIGINAL.md. © VeriSafe.Live}