Paraphrase-GGUF / README.md
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metadata
license: apache-2.0
language: en
tags:
  - text-generation
  - paraphrasing
  - transformer
  - TensorBlock
  - GGUF
datasets:
  - SQUAD
pipeline_tag: text2text-generation
base_model: SRDdev/Paraphrase
TensorBlock

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SRDdev/Paraphrase - GGUF

This repo contains GGUF format model files for SRDdev/Paraphrase.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

Our projects

Awesome MCP Servers TensorBlock Studio
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A comprehensive collection of Model Context Protocol (MCP) servers. A lightweight, open, and extensible multi-LLM interaction studio.
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## Prompt template

Model file specification

Filename Quant type File Size Description
Paraphrase-Q2_K.gguf Q2_K 0.103 GB smallest, significant quality loss - not recommended for most purposes
Paraphrase-Q3_K_S.gguf Q3_K_S 0.117 GB very small, high quality loss
Paraphrase-Q3_K_M.gguf Q3_K_M 0.128 GB very small, high quality loss
Paraphrase-Q3_K_L.gguf Q3_K_L 0.137 GB small, substantial quality loss
Paraphrase-Q4_0.gguf Q4_0 0.147 GB legacy; small, very high quality loss - prefer using Q3_K_M
Paraphrase-Q4_K_S.gguf Q4_K_S 0.147 GB small, greater quality loss
Paraphrase-Q4_K_M.gguf Q4_K_M 0.161 GB medium, balanced quality - recommended
Paraphrase-Q5_0.gguf Q5_0 0.175 GB legacy; medium, balanced quality - prefer using Q4_K_M
Paraphrase-Q5_K_S.gguf Q5_K_S 0.175 GB large, low quality loss - recommended
Paraphrase-Q5_K_M.gguf Q5_K_M 0.182 GB large, very low quality loss - recommended
Paraphrase-Q6_K.gguf Q6_K 0.204 GB very large, extremely low quality loss
Paraphrase-Q8_0.gguf Q8_0 0.264 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/Paraphrase-GGUF --include "Paraphrase-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/Paraphrase-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'