DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored-MNN

Pre-converted DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored in MNN format for on-device inference with TokForge.

Original model by aifeifei798 β€” converted to MNN Q4 for mobile deployment.

Model Details

Architecture Llama 3.1 (standard attention, 32 layers, GQA 32Q/8KV)
Parameters 8B (4-bit quantized)
Format MNN (Alibaba Mobile Neural Network)
Quantization W4A16 (4-bit weights, block size 128)
Vocab 128,256 tokens
Source aifeifei798/DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored

Description

DarkIdol v1.2 by aifeifei798 β€” a popular uncensored Llama 3.1 fine-tune optimized for roleplay, creative writing, and unrestricted conversation. Part of the DarkIdol series known for strong character adherence and expressive output.

Files

File Description
llm.mnn Model computation graph
llm.mnn.weight Quantized weight data (Q4, block=128)
llm_config.json Model config with Jinja chat template
tokenizer.txt Tokenizer vocabulary
config.json MNN runtime config

Usage with TokForge

This model is optimized for TokForge β€” a free Android app for private, on-device LLM inference.

  1. Download TokForge from the Play Store
  2. Open the app β†’ Models β†’ Download this model
  3. Start chatting β€” runs 100% locally, no internet required

Recommended Settings

Setting Value
Backend OpenCL (Qualcomm) / Vulkan (MediaTek) / CPU (fallback)
Precision Low
Threads 4
Thinking Off (or On for thinking-capable models)

Performance

Actual speed varies by device, thermal state, and generation length. Typical ranges for this model size:

Device SoC Backend tok/s
RedMagic 11 Pro SM8850 OpenCL 14.7 tok/s

Attribution

This is an MNN conversion of DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored by aifeifei798. All credit for the model architecture, training, and fine-tuning goes to the original author(s). This conversion only changes the runtime format for mobile deployment.

Limitations

  • Intended for TokForge / MNN on-device inference on Android
  • This is a runtime bundle, not a standard Transformers training checkpoint
  • Quantization (Q4) may slightly reduce quality compared to the full-precision original
  • Abliterated/uncensored models have had safety filters removed β€” use responsibly

Community

Export Details

Converted using MNN's llmexport pipeline:

python llmexport.py --path aifeifei798/DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored --export mnn --quant_bit 4 --quant_block 128
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