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metadata
library_name: transformers
base_model: realtreetune/rho-1b-sft-GSM8K
tags:
  - TensorBlock
  - GGUF
TensorBlock

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realtreetune/rho-1b-sft-GSM8K - GGUF

This repo contains GGUF format model files for realtreetune/rho-1b-sft-GSM8K.

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

Prompt template


Model file specification

Filename Quant type File Size Description
rho-1b-sft-GSM8K-Q2_K.gguf Q2_K 0.402 GB smallest, significant quality loss - not recommended for most purposes
rho-1b-sft-GSM8K-Q3_K_S.gguf Q3_K_S 0.465 GB very small, high quality loss
rho-1b-sft-GSM8K-Q3_K_M.gguf Q3_K_M 0.511 GB very small, high quality loss
rho-1b-sft-GSM8K-Q3_K_L.gguf Q3_K_L 0.551 GB small, substantial quality loss
rho-1b-sft-GSM8K-Q4_0.gguf Q4_0 0.593 GB legacy; small, very high quality loss - prefer using Q3_K_M
rho-1b-sft-GSM8K-Q4_K_S.gguf Q4_K_S 0.596 GB small, greater quality loss
rho-1b-sft-GSM8K-Q4_K_M.gguf Q4_K_M 0.622 GB medium, balanced quality - recommended
rho-1b-sft-GSM8K-Q5_0.gguf Q5_0 0.713 GB legacy; medium, balanced quality - prefer using Q4_K_M
rho-1b-sft-GSM8K-Q5_K_S.gguf Q5_K_S 0.713 GB large, low quality loss - recommended
rho-1b-sft-GSM8K-Q5_K_M.gguf Q5_K_M 0.728 GB large, very low quality loss - recommended
rho-1b-sft-GSM8K-Q6_K.gguf Q6_K 0.841 GB very large, extremely low quality loss
rho-1b-sft-GSM8K-Q8_0.gguf Q8_0 1.089 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/rho-1b-sft-GSM8K-GGUF --include "rho-1b-sft-GSM8K-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/rho-1b-sft-GSM8K-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'