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PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct-Q4_K_M-GGUF
Llama-3-Patronus-Lynx-8B-Instruct-Q4_K_M-GGUF is a machine learning model from PatronusAI. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as cc-by-nc-4.0.
This model is a quantized version of PatronusAI/Patronus-Lynx-8B-Instruct. Refer to the original model card for more details on the model.
Downloads · 30 days
159
2% of all-time downloads
All-time downloads
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.gguf4.9 GB · 100%
From the Hugging Face model README
This model is a quantized version of PatronusAI/Patronus-Lynx-8B-Instruct.
Refer to the original model card for more details on the model.
License: https://creativecommons.org/licenses/by-nc/4.0/
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
llama-cli --hf-repo PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct-Q4_K_M-GGUF --hf-file patronus-lynx-8b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
llama-server --hf-repo PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct-Q4_K_M-GGUF --hf-file patronus-lynx-8b-instruct-q4_k_m.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./llama-cli --hf-repo PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct-Q4_K_M-GGUF --hf-file patronus-lynx-8b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct-Q4_K_M-GGUF --hf-file patronus-lynx-8b-instruct-q4_k_m.gguf -c 2048