GGUF
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GGUF
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allenai/OLMo-1B-hf - GGUF

This repo contains GGUF format model files for allenai/OLMo-1B-hf.

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

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## Prompt template

Model file specification

Filename Quant type File Size Description
OLMo-1B-hf-Q2_K.gguf Q2_K 0.447 GB smallest, significant quality loss - not recommended for most purposes
OLMo-1B-hf-Q3_K_S.gguf Q3_K_S 0.510 GB very small, high quality loss
OLMo-1B-hf-Q3_K_M.gguf Q3_K_M 0.563 GB very small, high quality loss
OLMo-1B-hf-Q3_K_L.gguf Q3_K_L 0.607 GB small, substantial quality loss
OLMo-1B-hf-Q4_0.gguf Q4_0 0.643 GB legacy; small, very high quality loss - prefer using Q3_K_M
OLMo-1B-hf-Q4_K_S.gguf Q4_K_S 0.649 GB small, greater quality loss
OLMo-1B-hf-Q4_K_M.gguf Q4_K_M 0.683 GB medium, balanced quality - recommended
OLMo-1B-hf-Q5_0.gguf Q5_0 0.768 GB legacy; medium, balanced quality - prefer using Q4_K_M
OLMo-1B-hf-Q5_K_S.gguf Q5_K_S 0.768 GB large, low quality loss - recommended
OLMo-1B-hf-Q5_K_M.gguf Q5_K_M 0.789 GB large, very low quality loss - recommended
OLMo-1B-hf-Q6_K.gguf Q6_K 0.901 GB very large, extremely low quality loss
OLMo-1B-hf-Q8_0.gguf Q8_0 1.166 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/OLMo-1B-hf-GGUF --include "OLMo-1B-hf-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/OLMo-1B-hf-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
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GGUF
Model size
1.18B params
Architecture
olmo
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Model tree for tensorblock/OLMo-1B-hf-GGUF

Base model

allenai/OLMo-1B-hf
Quantized
(5)
this model

Dataset used to train tensorblock/OLMo-1B-hf-GGUF