gpt2-large-GGUF / README.md
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metadata
language: en
license: mit
tags:
  - TensorBlock
  - GGUF
base_model: openai-community/gpt2-large
TensorBlock

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openai-community/gpt2-large - GGUF

This repo contains GGUF format model files for openai-community/gpt2-large.

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
gpt2-large-Q2_K.gguf Q2_K 0.322 GB smallest, significant quality loss - not recommended for most purposes
gpt2-large-Q3_K_S.gguf Q3_K_S 0.367 GB very small, high quality loss
gpt2-large-Q3_K_M.gguf Q3_K_M 0.427 GB very small, high quality loss
gpt2-large-Q3_K_L.gguf Q3_K_L 0.460 GB small, substantial quality loss
gpt2-large-Q4_0.gguf Q4_0 0.462 GB legacy; small, very high quality loss - prefer using Q3_K_M
gpt2-large-Q4_K_S.gguf Q4_K_S 0.465 GB small, greater quality loss
gpt2-large-Q4_K_M.gguf Q4_K_M 0.511 GB medium, balanced quality - recommended
gpt2-large-Q5_0.gguf Q5_0 0.552 GB legacy; medium, balanced quality - prefer using Q4_K_M
gpt2-large-Q5_K_S.gguf Q5_K_S 0.552 GB large, low quality loss - recommended
gpt2-large-Q5_K_M.gguf Q5_K_M 0.589 GB large, very low quality loss - recommended
gpt2-large-Q6_K.gguf Q6_K 0.648 GB very large, extremely low quality loss
gpt2-large-Q8_0.gguf Q8_0 0.836 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/gpt2-large-GGUF --include "gpt2-large-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/gpt2-large-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'