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LLM360_K2-GGUF

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metadata
license: apache-2.0
language:
  - en
pipeline_tag: text-generation
library_name: transformers
tags:
  - nlp
  - llm
  - TensorBlock
  - GGUF
base_model: LLM360/K2
TensorBlock

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LLM360/K2 - GGUF

This repo contains GGUF format model files for LLM360/K2.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5165.

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Prompt template 

Unable to determine prompt format automatically. Please check the original model repository for the correct prompt format.

Model file specification

Filename Quant type File Size Description
K2-Q2_K.gguf Q2_K 24.113 GB smallest, significant quality loss - not recommended for most purposes
K2-Q3_K_S.gguf Q3_K_S 28.161 GB very small, high quality loss
K2-Q3_K_M.gguf Q3_K_M 31.632 GB very small, high quality loss
K2-Q3_K_L.gguf Q3_K_L 34.649 GB small, substantial quality loss
K2-Q4_0.gguf Q4_0 36.796 GB legacy; small, very high quality loss - prefer using Q3_K_M
K2-Q4_K_S.gguf Q4_K_S 37.055 GB small, greater quality loss
K2-Q4_K_M.gguf Q4_K_M 39.348 GB medium, balanced quality - recommended
K2-Q5_0.gguf Q5_0 44.924 GB legacy; medium, balanced quality - prefer using Q4_K_M
K2-Q5_K_S.gguf Q5_K_S 44.924 GB large, low quality loss - recommended
K2-Q5_K_M.gguf Q5_K_M 46.239 GB large, very low quality loss - recommended
K2-Q6_K Q6_K 53.560 GB very large, extremely low quality loss
K2-Q8_0 Q8_0 69.371 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/LLM360_K2-GGUF --include "K2-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/LLM360_K2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'