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pythia-160m-GGUF

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metadata
language:
  - en
tags:
  - pytorch
  - causal-lm
  - pythia
  - TensorBlock
  - GGUF
license: apache-2.0
datasets:
  - EleutherAI/pile
base_model: EleutherAI/pythia-160m
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EleutherAI/pythia-160m - GGUF

This repo contains GGUF format model files for EleutherAI/pythia-160m.

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
pythia-160m-Q2_K.gguf Q2_K 0.073 GB smallest, significant quality loss - not recommended for most purposes
pythia-160m-Q3_K_S.gguf Q3_K_S 0.081 GB very small, high quality loss
pythia-160m-Q3_K_M.gguf Q3_K_M 0.088 GB very small, high quality loss
pythia-160m-Q3_K_L.gguf Q3_K_L 0.092 GB small, substantial quality loss
pythia-160m-Q4_0.gguf Q4_0 0.096 GB legacy; small, very high quality loss - prefer using Q3_K_M
pythia-160m-Q4_K_S.gguf Q4_K_S 0.097 GB small, greater quality loss
pythia-160m-Q4_K_M.gguf Q4_K_M 0.102 GB medium, balanced quality - recommended
pythia-160m-Q5_0.gguf Q5_0 0.111 GB legacy; medium, balanced quality - prefer using Q4_K_M
pythia-160m-Q5_K_S.gguf Q5_K_S 0.111 GB large, low quality loss - recommended
pythia-160m-Q5_K_M.gguf Q5_K_M 0.115 GB large, very low quality loss - recommended
pythia-160m-Q6_K.gguf Q6_K 0.126 GB very large, extremely low quality loss
pythia-160m-Q8_0.gguf Q8_0 0.163 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/pythia-160m-GGUF --include "pythia-160m-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/pythia-160m-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'