ThijsL202/NegativePharaoh_DSR1-LLAMA-70B-IQ4_XS-GGUF

        # ThijsL202/NegativePharaoh_DSR1-LLAMA-70B-IQ4_XS-GGUF
        This model was converted to GGUF format from [ThijsL202/NegativePharaoh_DSR1-LLAMA-70B](https://huggingface.co/ThijsL202/NegativePharaoh_DSR1-LLAMA-70B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
        Refer to the [original model card](https://huggingface.co/ThijsL202/NegativePharaoh_DSR1-LLAMA-70B) for more details on the model.

        ## Use with llama.cpp
        Install llama.cpp through brew (works on Mac and Linux)

bash brew install llama.cpp

        Invoke the llama.cpp server or the CLI.

        ### CLI:

bash llama-cli --hf-repo ThijsL202/NegativePharaoh_DSR1-LLAMA-70B-IQ4_XS-GGUF --hf-file negativepharaoh_dsr1-llama-70b-iq4_xs-imat.gguf -p "The meaning to life and the universe is"

        ### Server:

bash llama-server --hf-repo ThijsL202/NegativePharaoh_DSR1-LLAMA-70B-IQ4_XS-GGUF --hf-file negativepharaoh_dsr1-llama-70b-iq4_xs-imat.gguf -c 2048

        Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
        Step 1: Clone llama.cpp from GitHub.

bash 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).

bash cd llama.cpp && LLAMA_CURL=1 make

        Step 3: Run inference through the main binary.

bash ./llama-cli --hf-repo ThijsL202/NegativePharaoh_DSR1-LLAMA-70B-IQ4_XS-GGUF --hf-file negativepharaoh_dsr1-llama-70b-iq4_xs-imat.gguf -p "The meaning to life and the universe is"

        or 

bash ./llama-server --hf-repo ThijsL202/NegativePharaoh_DSR1-LLAMA-70B-IQ4_XS-GGUF --hf-file negativepharaoh_dsr1-llama-70b-iq4_xs-imat.gguf -c 2048