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metadata
language:
  - en
  - de
  - fr
  - zh
  - pt
  - nl
  - ru
  - ko
  - it
  - es
license: cc-by-nc-4.0
metrics:
  - comet
pipeline_tag: translation
base_model: Unbabel/TowerInstruct-7B-v0.2
tags:
  - TensorBlock
  - GGUF
TensorBlock

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Unbabel/TowerInstruct-7B-v0.2 - GGUF

This repo contains GGUF format model files for Unbabel/TowerInstruct-7B-v0.2.

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
TowerInstruct-7B-v0.2-Q2_K.gguf Q2_K 2.359 GB smallest, significant quality loss - not recommended for most purposes
TowerInstruct-7B-v0.2-Q3_K_S.gguf Q3_K_S 2.746 GB very small, high quality loss
TowerInstruct-7B-v0.2-Q3_K_M.gguf Q3_K_M 3.072 GB very small, high quality loss
TowerInstruct-7B-v0.2-Q3_K_L.gguf Q3_K_L 3.350 GB small, substantial quality loss
TowerInstruct-7B-v0.2-Q4_0.gguf Q4_0 3.563 GB legacy; small, very high quality loss - prefer using Q3_K_M
TowerInstruct-7B-v0.2-Q4_K_S.gguf Q4_K_S 3.592 GB small, greater quality loss
TowerInstruct-7B-v0.2-Q4_K_M.gguf Q4_K_M 3.801 GB medium, balanced quality - recommended
TowerInstruct-7B-v0.2-Q5_0.gguf Q5_0 4.332 GB legacy; medium, balanced quality - prefer using Q4_K_M
TowerInstruct-7B-v0.2-Q5_K_S.gguf Q5_K_S 4.332 GB large, low quality loss - recommended
TowerInstruct-7B-v0.2-Q5_K_M.gguf Q5_K_M 4.455 GB large, very low quality loss - recommended
TowerInstruct-7B-v0.2-Q6_K.gguf Q6_K 5.150 GB very large, extremely low quality loss
TowerInstruct-7B-v0.2-Q8_0.gguf Q8_0 6.669 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/TowerInstruct-7B-v0.2-GGUF --include "TowerInstruct-7B-v0.2-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/TowerInstruct-7B-v0.2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'