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metadata
license: cc-by-sa-4.0
datasets:
  - maywell/ko_wikidata_QA
  - kyujinpy/OpenOrca-KO
language:
  - en
  - ko
pipeline_tag: text-generation
base_model: maywell/PiVoT-0.1-early
tags:
  - TensorBlock
  - GGUF
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maywell/PiVoT-0.1-early - GGUF

This repo contains GGUF format model files for maywell/PiVoT-0.1-early.

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

Prompt template 

<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Model file specification

Filename Quant type File Size Description
PiVoT-0.1-early-Q2_K.gguf Q2_K 2.533 GB smallest, significant quality loss - not recommended for most purposes
PiVoT-0.1-early-Q3_K_S.gguf Q3_K_S 2.947 GB very small, high quality loss
PiVoT-0.1-early-Q3_K_M.gguf Q3_K_M 3.277 GB very small, high quality loss
PiVoT-0.1-early-Q3_K_L.gguf Q3_K_L 3.560 GB small, substantial quality loss
PiVoT-0.1-early-Q4_0.gguf Q4_0 3.827 GB legacy; small, very high quality loss - prefer using Q3_K_M
PiVoT-0.1-early-Q4_K_S.gguf Q4_K_S 3.856 GB small, greater quality loss
PiVoT-0.1-early-Q4_K_M.gguf Q4_K_M 4.068 GB medium, balanced quality - recommended
PiVoT-0.1-early-Q5_0.gguf Q5_0 4.654 GB legacy; medium, balanced quality - prefer using Q4_K_M
PiVoT-0.1-early-Q5_K_S.gguf Q5_K_S 4.654 GB large, low quality loss - recommended
PiVoT-0.1-early-Q5_K_M.gguf Q5_K_M 4.779 GB large, very low quality loss - recommended
PiVoT-0.1-early-Q6_K.gguf Q6_K 5.534 GB very large, extremely low quality loss
PiVoT-0.1-early-Q8_0.gguf Q8_0 7.167 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/PiVoT-0.1-early-GGUF --include "PiVoT-0.1-early-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/PiVoT-0.1-early-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'