Edit model card
TensorBlock

Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server

allenai/OLMoE-1B-7B-0924-Instruct - GGUF

This repo contains GGUF format model files for allenai/OLMoE-1B-7B-0924-Instruct.

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

Prompt template

<|endoftext|><|system|>
{system_prompt}
<|user|>
{prompt}
<|assistant|>

Model file specification

Filename Quant type File Size Description
OLMoE-1B-7B-0924-Instruct-Q2_K.gguf Q2_K 2.387 GB smallest, significant quality loss - not recommended for most purposes
OLMoE-1B-7B-0924-Instruct-Q3_K_S.gguf Q3_K_S 2.815 GB very small, high quality loss
OLMoE-1B-7B-0924-Instruct-Q3_K_M.gguf Q3_K_M 3.114 GB very small, high quality loss
OLMoE-1B-7B-0924-Instruct-Q3_K_L.gguf Q3_K_L 3.363 GB small, substantial quality loss
OLMoE-1B-7B-0924-Instruct-Q4_0.gguf Q4_0 3.658 GB legacy; small, very high quality loss - prefer using Q3_K_M
OLMoE-1B-7B-0924-Instruct-Q4_K_S.gguf Q4_K_S 3.691 GB small, greater quality loss
OLMoE-1B-7B-0924-Instruct-Q4_K_M.gguf Q4_K_M 3.924 GB medium, balanced quality - recommended
OLMoE-1B-7B-0924-Instruct-Q5_0.gguf Q5_0 4.452 GB legacy; medium, balanced quality - prefer using Q4_K_M
OLMoE-1B-7B-0924-Instruct-Q5_K_S.gguf Q5_K_S 4.452 GB large, low quality loss - recommended
OLMoE-1B-7B-0924-Instruct-Q5_K_M.gguf Q5_K_M 4.588 GB large, very low quality loss - recommended
OLMoE-1B-7B-0924-Instruct-Q6_K.gguf Q6_K 5.294 GB very large, extremely low quality loss
OLMoE-1B-7B-0924-Instruct-Q8_0.gguf Q8_0 6.854 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/OLMoE-1B-7B-0924-Instruct-GGUF --include "OLMoE-1B-7B-0924-Instruct-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/OLMoE-1B-7B-0924-Instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
237
GGUF
Model size
6.92B params
Architecture
olmoe

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for tensorblock/OLMoE-1B-7B-0924-Instruct-GGUF

Quantized
(9)
this model

Dataset used to train tensorblock/OLMoE-1B-7B-0924-Instruct-GGUF