darkmaniac7/Qwen3-4B-abliterated-MNN

Source: 🤗text-generationapache-2.04B activated2.5 GBother✓ 2 checksumsupdated 9d ago
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Published by TokForge for on-device inference.

TokForge

Runs on-device in the TokForge app.

Qwen3-4B Abliterated MNN

MNN 4-bit HQQ quantized model for TokForge on-device inference.

Model Info

Parameters 4B
Quantization 4-bit HQQ (quant_block=64)
Size 2.4GB
Source huihui-ai/Huihui-Qwen3-4B-abliterated-v2
Backend MNN OpenCL (GPU-accelerated)
Min RAM 8GB+

Speculative Decoding

This model is compatible with the TokForge Acceleration Pack (Qwen3-0.6B draft model), which works with both censored and abliterated targets.

Usage

Download via TokForge app → Models → Roleplay category, or manually place files in the TokForge models directory.

Limitations and Intended Use

  • Intended for TokForge / MNN mobile inference.
  • 4B was not the strongest speculative-decoding target in our later preserved fleet results.
  • Performance depends strongly on SoC, backend routing, and device thermal behavior.
  • This repo is a runtime/export artifact, not a standard Transformers release.

Files

  • llm.mnn: Model graph
  • llm.mnn.weight: Quantized weights
  • tokenizer.txt: Tokenizer vocabulary
  • llm_config.json: Model configuration
  • embeddings_bf16.bin: Embedding table (8B/14B only)

Credits

  • Huihui-Qwen3-4B-abliterated-v2 by huihui-ai (Hugging Face). Used under the Apache-2.0 license.
  • Qwen3-4B by the Qwen team (Alibaba Cloud) (Hugging Face). Used under the Apache-2.0 license.
  • Converted with llmexport from MNN by Alibaba (Apache-2.0).

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