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darkmaniac7/DeepSeek-R1-Distill-Llama-8B-MNN
DeepSeek-R1-Distill-Llama-8B-MNN is a text generation model from darkmaniac7. Use it when you need the model to write or continue text. The card lists the license as mit.
Published by TokForge for on-device inference.
Downloads · 30 days
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18% of all-time downloads
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From the Hugging Face model README
Published by TokForge for on-device inference.
Runs on-device in the TokForge app.
Pre-converted DeepSeek R1 Distill Llama 8B in MNN format for on-device inference with TokForge.
Original model by DeepSeek, converted to MNN Q4 for mobile deployment.
| Architecture | Llama 3.1 (standard attention, 32 layers, GQA, distilled from DeepSeek-R1) |
| Parameters | 8B (4-bit quantized) |
| Format | MNN (Alibaba Mobile Neural Network) |
| Quantization | W4A16 (4-bit weights, block size 128) |
| Vocab | 128,256 tokens |
| Source | deepseek-ai/DeepSeek-R1-Distill-Llama-8B |
DeepSeek's R1 reasoning capability distilled into a Llama 3.1 8B body. Brings chain-of-thought reasoning to mobile devices. Shows its thinking process step-by-step, making it excellent for math, logic puzzles, coding, and complex analysis.
| 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 |
This model is optimized for TokForge, a free Android app for private, on-device LLM inference.
| Setting | Value |
|---|---|
| Backend | OpenCL (Qualcomm) / Vulkan (MediaTek) / CPU (fallback) |
| Precision | Low |
| Threads | 4 |
| Thinking | Off (or On for thinking-capable models) |
LICENSE and NOTICE files in this repo.Converted using MNN's llmexport pipeline:
python llmexport.py --path deepseek-ai/DeepSeek-R1-Distill-Llama-8B --export mnn --quant_bit 4 --quant_block 128