tensorblock/rank_zephyr_7b_v1_full-GGUF

🤗 Hugging Face sourcetext-rankingmit7B activated55 GBGGUF✓ 2 checksumsupdated today
Submit in one command

Run it next to your model folder. It makes the torrent, checks your files against Hugging Face, and submits it. You just start seeding and paste your key from your account. It only reads your files and never changes them. Read the script first if you like.

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo tensorblock/rank_zephyr_7b_v1_full-GGUF ./model-folder
Needs a seeder →

castorini/rank_zephyr_7b_v1_full - GGUF

This repo contains GGUF format model files for castorini/rank_zephyr_7b_v1_full.

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

Our projects

Forge
An OpenAI-compatible multi-provider routing layer.
🚀 Try it now! 🚀
Awesome MCP Servers TensorBlock Studio
A comprehensive collection of Model Context Protocol (MCP) servers. A lightweight, open, and extensible multi-LLM interaction studio.
👀 See what we built 👀 👀 See what we built 👀
## Prompt template
<|system|>
{system_prompt}</s>
<|user|>
{prompt}</s>
<|assistant|>

Model file specification

Filename Quant type File Size Description
rank_zephyr_7b_v1_full-Q2_K.gguf Q2_K 2.532 GB smallest, significant quality loss - not recommended for most purposes
rank_zephyr_7b_v1_full-Q3_K_S.gguf Q3_K_S 2.947 GB very small, high quality loss
rank_zephyr_7b_v1_full-Q3_K_M.gguf Q3_K_M 3.277 GB very small, high quality loss
rank_zephyr_7b_v1_full-Q3_K_L.gguf Q3_K_L 3.560 GB small, substantial quality loss
rank_zephyr_7b_v1_full-Q4_0.gguf Q4_0 3.827 GB legacy; small, very high quality loss - prefer using Q3_K_M
rank_zephyr_7b_v1_full-Q4_K_S.gguf Q4_K_S 3.856 GB small, greater quality loss
rank_zephyr_7b_v1_full-Q4_K_M.gguf Q4_K_M 4.068 GB medium, balanced quality - recommended
rank_zephyr_7b_v1_full-Q5_0.gguf Q5_0 4.654 GB legacy; medium, balanced quality - prefer using Q4_K_M
rank_zephyr_7b_v1_full-Q5_K_S.gguf Q5_K_S 4.654 GB large, low quality loss - recommended
rank_zephyr_7b_v1_full-Q5_K_M.gguf Q5_K_M 4.779 GB large, very low quality loss - recommended
rank_zephyr_7b_v1_full-Q6_K.gguf Q6_K 5.534 GB very large, extremely low quality loss
rank_zephyr_7b_v1_full-Q8_0.gguf Q8_0 7.167 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/rank_zephyr_7b_v1_full-GGUF --include "rank_zephyr_7b_v1_full-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/rank_zephyr_7b_v1_full-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'