tensorblock/phillama-prune3-GGUF

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aipib/phillama-prune3 - GGUF

This repo contains GGUF format model files for aipib/phillama-prune3.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

Run them on the TensorBlock client using your local machine ↗

Prompt template

<s><|system|>
{system_prompt}<|end|>
<|user|>
{prompt}<|end|>
<|assistant|>

Model file specification

Filename	Quant type	File Size	Description
phillama-prune3-Q2_K.gguf	Q2_K	1.280 GB	smallest, significant quality loss - not recommended for most purposes
phillama-prune3-Q3_K_S.gguf	Q3_K_S	1.487 GB	very small, high quality loss
phillama-prune3-Q3_K_M.gguf	Q3_K_M	1.656 GB	very small, high quality loss
phillama-prune3-Q3_K_L.gguf	Q3_K_L	1.805 GB	small, substantial quality loss
phillama-prune3-Q4_0.gguf	Q4_0	1.921 GB	legacy; small, very high quality loss - prefer using Q3_K_M
phillama-prune3-Q4_K_S.gguf	Q4_K_S	1.935 GB	small, greater quality loss
phillama-prune3-Q4_K_M.gguf	Q4_K_M	2.046 GB	medium, balanced quality - recommended
phillama-prune3-Q5_0.gguf	Q5_0	2.330 GB	legacy; medium, balanced quality - prefer using Q4_K_M
phillama-prune3-Q5_K_S.gguf	Q5_K_S	2.330 GB	large, low quality loss - recommended
phillama-prune3-Q5_K_M.gguf	Q5_K_M	2.394 GB	large, very low quality loss - recommended
phillama-prune3-Q6_K.gguf	Q6_K	2.764 GB	very large, extremely low quality loss
phillama-prune3-Q8_0.gguf	Q8_0	3.580 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/phillama-prune3-GGUF --include "phillama-prune3-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/phillama-prune3-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'