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stabilityai/stablelm-3b-4e1t - GGUF

This repo contains GGUF format model files for stabilityai/stablelm-3b-4e1t.

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
stablelm-3b-4e1t-Q2_K.gguf Q2_K 1.009 GB smallest, significant quality loss - not recommended for most purposes
stablelm-3b-4e1t-Q3_K_S.gguf Q3_K_S 1.168 GB very small, high quality loss
stablelm-3b-4e1t-Q3_K_M.gguf Q3_K_M 1.296 GB very small, high quality loss
stablelm-3b-4e1t-Q3_K_L.gguf Q3_K_L 1.405 GB small, substantial quality loss
stablelm-3b-4e1t-Q4_0.gguf Q4_0 1.498 GB legacy; small, very high quality loss - prefer using Q3_K_M
stablelm-3b-4e1t-Q4_K_S.gguf Q4_K_S 1.509 GB small, greater quality loss
stablelm-3b-4e1t-Q4_K_M.gguf Q4_K_M 1.591 GB medium, balanced quality - recommended
stablelm-3b-4e1t-Q5_0.gguf Q5_0 1.809 GB legacy; medium, balanced quality - prefer using Q4_K_M
stablelm-3b-4e1t-Q5_K_S.gguf Q5_K_S 1.809 GB large, low quality loss - recommended
stablelm-3b-4e1t-Q5_K_M.gguf Q5_K_M 1.856 GB large, very low quality loss - recommended
stablelm-3b-4e1t-Q6_K.gguf Q6_K 2.138 GB very large, extremely low quality loss
stablelm-3b-4e1t-Q8_0.gguf Q8_0 2.769 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/stablelm-3b-4e1t-GGUF --include "stablelm-3b-4e1t-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/stablelm-3b-4e1t-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
260
GGUF
Model size
2.8B params
Architecture
stablelm

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Inference API
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Model tree for tensorblock/stablelm-3b-4e1t-GGUF

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Datasets used to train tensorblock/stablelm-3b-4e1t-GGUF

Evaluation results