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allenai/OLMo-7B-hf - GGUF

This repo contains GGUF format model files for allenai/OLMo-7B-hf.

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
OLMo-7B-hf-Q2_K.gguf Q2_K 2.439 GB smallest, significant quality loss - not recommended for most purposes
OLMo-7B-hf-Q3_K_S.gguf Q3_K_S 2.833 GB very small, high quality loss
OLMo-7B-hf-Q3_K_M.gguf Q3_K_M 3.159 GB very small, high quality loss
OLMo-7B-hf-Q3_K_L.gguf Q3_K_L 3.437 GB small, substantial quality loss
OLMo-7B-hf-Q4_0.gguf Q4_0 3.660 GB legacy; small, very high quality loss - prefer using Q3_K_M
OLMo-7B-hf-Q4_K_S.gguf Q4_K_S 3.688 GB small, greater quality loss
OLMo-7B-hf-Q4_K_M.gguf Q4_K_M 3.897 GB medium, balanced quality - recommended
OLMo-7B-hf-Q5_0.gguf Q5_0 4.437 GB legacy; medium, balanced quality - prefer using Q4_K_M
OLMo-7B-hf-Q5_K_S.gguf Q5_K_S 4.437 GB large, low quality loss - recommended
OLMo-7B-hf-Q5_K_M.gguf Q5_K_M 4.560 GB large, very low quality loss - recommended
OLMo-7B-hf-Q6_K.gguf Q6_K 5.264 GB very large, extremely low quality loss
OLMo-7B-hf-Q8_0.gguf Q8_0 6.818 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-7B-hf-GGUF --include "OLMo-7B-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-7B-hf-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
32
GGUF
Model size
6.89B params
Architecture
olmo

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Inference API
Unable to determine this model's library. Check the docs .

Model tree for tensorblock/OLMo-7B-hf-GGUF

Base model

allenai/OLMo-7B-hf
Quantized
(3)
this model

Dataset used to train tensorblock/OLMo-7B-hf-GGUF