Llama Guard 3 8B IMat GGUF

🚀 Llama-Guard-3-8B-IMat-GGUF

Llama.cpp imatrix quantization of meta-llama/Llama-Guard-3-8B

This project offers the Llama.cpp imatrix quantization of the meta-llama/Llama-Guard-3-8B model, providing various quantized versions for different needs.

Original Model: meta-llama/Llama-Guard-3-8B
Original dtype: BF16 (bfloat16)
Quantized by: llama.cpp b3447
IMatrix dataset: here

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

📚 Documentation

Files

IMatrix

Status: ✅ Available
Link: here

Common Quants

All Quants

Downloading using huggingface-cli

You can use the huggingface-cli to download the quantized models. Here is a general example:

huggingface-cli download <model_name> <filename>

Replace <model_name> with legraphista/Llama-Guard-3-8B-IMat-GGUF and <filename> with the specific quantized model file you want to download.

Inference

Simple chat template

For a simple chat scenario, you can use the following template:

<|InnerThoughtBegin|>The user needs a response, use the Llama model to generate one.<|InnerThoughtEnd|><|FunctionCallBegin|>[{"name": "llama_generate", "parameters": {"input": "<user_question>"}}]<|FunctionCallEnd|>

Replace <user_question> with the actual question from the user.

Llama.cpp

To perform inference using llama.cpp, you can follow these steps:

1. Clone the llama.cpp repository:

git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp

2. Build the project:

make

3. Run inference with a quantized model:

./main -m <path_to_gguf_file> -p "<prompt>"

Replace <path_to_gguf_file> with the path to the downloaded quantized GGUF file and <prompt> with your input prompt.

FAQ

Why is the IMatrix not applied everywhere?

The IMatrix quantization might not be applied everywhere due to various reasons. Some quantized versions are designed to use static quantization for better compatibility or performance in certain scenarios. Additionally, the IMatrix dataset might not be suitable for all quantization levels or model architectures.

How do I merge a split GGUF?

If you have a split GGUF file and need to merge it, you can use the following steps:

1. Make sure you have all the split parts of the GGUF file.
2. Use a tool or script that supports merging GGUF files. You can refer to the official llama.cpp documentation or community resources for specific merging commands.

📄 License

This project is licensed under the llama3.1 license. The detailed license agreement is as follows:

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