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tecaprovn/deepseek-v4-flash-gguf

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DeepSeekV4Flash Quantization Repository

v4-benchmark-2

This repository provides scripts and guidelines for quantizing the DeepSeek V4 Flash model, enabling reduced model size and optimized inference performance.

v4-efficiency


🚀 Purpose

  • Reduce model size (BF16 → Q3/Q4/Q5/Q8, etc.)
  • Improve inference speed
  • Enable deployment on limited GPU/CPU resources

🌍 Languages

  • English (en)
  • Vietnamese (vi)

🧠 Base Model


📦 Contents

  • Model conversion and quantization scripts
  • Usage examples for llama.cpp / GGUF workflows
  • Common quantization configurations

🛠️ Requirements

  • Python >= 3.12
  • Latest version of llama.cpp (with GGUF support)
  • HuggingFace Transformers (if converting from HF format)
  • Sufficient RAM/VRAM depending on model size

⚙️ Example Usage

python convert_hf_to_gguf.py   --model deepseek-ai/DeepSeek-V4-Flash   --outfile models/DeepSeekV4Flash.gguf

./llama-quantize models/DeepSeekV4Flash.gguf Q4_K_M

📌 Notes

  • Quantization may require significant system memory depending on model size
  • Some quantization formats may not be compatible with all runtimes or versions
  • Always validate output quality after quantization

👤 Author


📄 License

This repository follows the original DeepSeek model license.

  • Base model: Apache 2.0 (DeepSeek)
  • Only conversion scripts included, no weight modification
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Model Info

Providertecaprovn
Categorygeneral
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