darkmaniac7 / Panth-L3-Blackroot-Nephra-8B-MNN

huggingface.co
Total runs: 171
24-hour runs: 0
7-day runs: -2
30-day runs: -34
Model's Last Updated: April 22 2026
text-generation

Introduction of Panth-L3-Blackroot-Nephra-8B-MNN

Model Details of Panth-L3-Blackroot-Nephra-8B-MNN

Panth-L3-Blackroot-Nephra-8B-MNN

Pre-converted Panth-L3-Blackroot-Nephra-MK.VI-8B in MNN format for on-device inference with TokForge .

Original model by mergekit-community — converted to MNN Q4 for mobile deployment.

Model Details
Architecture Llama 3 (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 mergekit-community/Panth-L3-Blackroot-Nephra-MK.VI-8B
Description

Panth-L3 Blackroot Nephra MK.VI — a Llama 3 8B merge by mergekit-community. Blends multiple fine-tunes for strong creative writing and roleplay capabilities.

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 — a free Android app for private, on-device LLM inference.

  1. Download TokForge from the Play Store
  2. Open the app → Models → Download this model
  3. Start chatting — 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 Panth-L3-Blackroot-Nephra-MK.VI-8B by mergekit-community . 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 — use responsibly
Community
Export Details

Converted using MNN's llmexport pipeline:

python llmexport.py --path mergekit-community/Panth-L3-Blackroot-Nephra-MK.VI-8B --export mnn --quant_bit 4 --quant_block 128

Runs of darkmaniac7 Panth-L3-Blackroot-Nephra-8B-MNN on huggingface.co

171
Total runs
0
24-hour runs
0
3-day runs
-2
7-day runs
-34
30-day runs

More Information About Panth-L3-Blackroot-Nephra-8B-MNN huggingface.co Model

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Panth-L3-Blackroot-Nephra-8B-MNN install

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