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Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-GGUF

Text Generation
GGUF
Korean
korean
llama3
instruction-tuning
dora
TensorBlock
GGUF
Inference Endpoints
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Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-GGUF / README.md
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metadata
license: llama3
language:
  - ko
tags:
  - korean
  - llama3
  - instruction-tuning
  - dora
  - TensorBlock
  - GGUF
datasets:
  - Acyrl
  - llm-kr-eval
  - Counter-MT-bench
base_model: AcrylaLLM/Llama-3-8B-Jonathan-aLLM-Instruct-v1.0
pipeline_tag: text-generation
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AcrylaLLM/Llama-3-8B-Jonathan-aLLM-Instruct-v1.0 - GGUF

This repo contains GGUF format model files for AcrylaLLM/Llama-3-8B-Jonathan-aLLM-Instruct-v1.0.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Prompt template

Model file specification

Filename Quant type File Size Description
Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-Q2_K.gguf Q2_K 3.179 GB smallest, significant quality loss - not recommended for most purposes
Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-Q3_K_S.gguf Q3_K_S 3.665 GB very small, high quality loss
Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-Q3_K_M.gguf Q3_K_M 4.019 GB very small, high quality loss
Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-Q3_K_L.gguf Q3_K_L 4.322 GB small, substantial quality loss
Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-Q4_0.gguf Q4_0 4.661 GB legacy; small, very high quality loss - prefer using Q3_K_M
Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-Q4_K_S.gguf Q4_K_S 4.693 GB small, greater quality loss
Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-Q4_K_M.gguf Q4_K_M 4.921 GB medium, balanced quality - recommended
Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-Q5_0.gguf Q5_0 5.599 GB legacy; medium, balanced quality - prefer using Q4_K_M
Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-Q5_K_S.gguf Q5_K_S 5.599 GB large, low quality loss - recommended
Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-Q5_K_M.gguf Q5_K_M 5.733 GB large, very low quality loss - recommended
Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-Q6_K.gguf Q6_K 6.596 GB very large, extremely low quality loss
Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-Q8_0.gguf Q8_0 8.541 GB very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-GGUF --include "Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/Llama-3-8B-Jonathan-aLLM-Instruct-v1.0-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'