metadata
license: cc-by-nc-4.0
language:
- ko
- en
pipeline_tag: text-generation
tags:
- meta
- llama-2
- llama-2-ko-en
- sheared llama
- TensorBlock
- GGUF
base_model: URP/urllm-ko_en-2.7b
Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
URP/urllm-ko_en-2.7b - GGUF
This repo contains GGUF format model files for URP/urllm-ko_en-2.7b.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
Prompt template
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
urllm-ko_en-2.7b-Q2_K.gguf | Q2_K | 1.086 GB | smallest, significant quality loss - not recommended for most purposes |
urllm-ko_en-2.7b-Q3_K_S.gguf | Q3_K_S | 1.257 GB | very small, high quality loss |
urllm-ko_en-2.7b-Q3_K_M.gguf | Q3_K_M | 1.394 GB | very small, high quality loss |
urllm-ko_en-2.7b-Q3_K_L.gguf | Q3_K_L | 1.511 GB | small, substantial quality loss |
urllm-ko_en-2.7b-Q4_0.gguf | Q4_0 | 1.611 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
urllm-ko_en-2.7b-Q4_K_S.gguf | Q4_K_S | 1.623 GB | small, greater quality loss |
urllm-ko_en-2.7b-Q4_K_M.gguf | Q4_K_M | 1.711 GB | medium, balanced quality - recommended |
urllm-ko_en-2.7b-Q5_0.gguf | Q5_0 | 1.945 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
urllm-ko_en-2.7b-Q5_K_S.gguf | Q5_K_S | 1.945 GB | large, low quality loss - recommended |
urllm-ko_en-2.7b-Q5_K_M.gguf | Q5_K_M | 1.996 GB | large, very low quality loss - recommended |
urllm-ko_en-2.7b-Q6_K.gguf | Q6_K | 2.299 GB | very large, extremely low quality loss |
urllm-ko_en-2.7b-Q8_0.gguf | Q8_0 | 2.978 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/urllm-ko_en-2.7b-GGUF --include "urllm-ko_en-2.7b-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/urllm-ko_en-2.7b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'