metadata
language:
- ko
tags:
- llama-2
- instruct
- instruction
- TensorBlock
- GGUF
pipeline_tag: text-generation
license: llama2
base_model: sanghwa-na/llama2-13b.kor.v1
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
sanghwa-na/llama2-13b.kor.v1 - GGUF
This repo contains GGUF format model files for sanghwa-na/llama2-13b.kor.v1.
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 |
|---|---|---|---|
| llama2-13b.kor.v1-Q2_K.gguf | Q2_K | 4.521 GB | smallest, significant quality loss - not recommended for most purposes |
| llama2-13b.kor.v1-Q3_K_S.gguf | Q3_K_S | 5.270 GB | very small, high quality loss |
| llama2-13b.kor.v1-Q3_K_M.gguf | Q3_K_M | 5.903 GB | very small, high quality loss |
| llama2-13b.kor.v1-Q3_K_L.gguf | Q3_K_L | 6.454 GB | small, substantial quality loss |
| llama2-13b.kor.v1-Q4_0.gguf | Q4_0 | 6.860 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| llama2-13b.kor.v1-Q4_K_S.gguf | Q4_K_S | 6.913 GB | small, greater quality loss |
| llama2-13b.kor.v1-Q4_K_M.gguf | Q4_K_M | 7.326 GB | medium, balanced quality - recommended |
| llama2-13b.kor.v1-Q5_0.gguf | Q5_0 | 8.356 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| llama2-13b.kor.v1-Q5_K_S.gguf | Q5_K_S | 8.356 GB | large, low quality loss - recommended |
| llama2-13b.kor.v1-Q5_K_M.gguf | Q5_K_M | 8.596 GB | large, very low quality loss - recommended |
| llama2-13b.kor.v1-Q6_K.gguf | Q6_K | 9.946 GB | very large, extremely low quality loss |
| llama2-13b.kor.v1-Q8_0.gguf | Q8_0 | 12.881 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/llama2-13b.kor.v1-GGUF --include "llama2-13b.kor.v1-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/llama2-13b.kor.v1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'