Minitron-4B-Base-GGUF

Minitron-4B-Base-GGUF

Llama.cpp static quantization of nvidia/Minitron-4B-Base

Original Model: nvidia/Minitron-4B-Base
Original dtype: BF16 (bfloat16)
Quantized by: llama.cpp b3600
IMatrix dataset: here

• Files
  • Common Quants
  • All Quants
• Downloading using huggingface-cli
• Inference
  • Llama.cpp
• FAQ
  • Why is the IMatrix not applied everywhere?
  • How do I merge a split GGUF?

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Files

Common Quants

All Quants

Downloading using huggingface-cli

If you do not have hugginface-cli installed:

pip install -U "huggingface_hub[cli]"

Download the specific file you want:

huggingface-cli download legraphista/Minitron-4B-Base-GGUF --include "Minitron-4B-Base.Q8_0.gguf" --local-dir ./

If the model file is big, it has been split into multiple files. In order to download them all to a local folder, run:

huggingface-cli download legraphista/Minitron-4B-Base-GGUF --include "Minitron-4B-Base.Q8_0/*" --local-dir ./
# see FAQ for merging GGUF's

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Inference

Llama.cpp

llama.cpp/main -m Minitron-4B-Base.Q8_0.gguf --color -i -p "prompt here"

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FAQ

Why is the IMatrix not applied everywhere?

According to this investigation, it appears that lower quantizations are the only ones that benefit from the imatrix input (as per hellaswag results).

How do I merge a split GGUF?

1. Make sure you have gguf-split available
   • To get hold of gguf-split, navigate to https://github.com/ggerganov/llama.cpp/releases
   • Download the appropriate zip for your system from the latest release
   • Unzip the archive and you should be able to find gguf-split
2. Locate your GGUF chunks folder (ex: Minitron-4B-Base.Q8_0)
3. Run gguf-split --merge Minitron-4B-Base.Q8_0/Minitron-4B-Base.Q8_0-00001-of-XXXXX.gguf Minitron-4B-Base.Q8_0.gguf
   • Make sure to point gguf-split to the first chunk of the split.

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