| --- |
| base_model: DesignSoft/TINA_AI3.4 |
| license: llama3.2 |
| tags: |
| - llama-cpp |
| - gguf-my-repo |
| --- |
| |
| # raimundsz/TINA_AI3.4-Q4_K_M-GGUF |
| This model was converted to GGUF format from [`DesignSoft/TINA_AI3.4`](https://huggingface.co/DesignSoft/TINA_AI3.4) 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/DesignSoft/TINA_AI3.4) 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 DesignSoft/TINA_AI3.4_Q4 --hf-file tina_ai3.4-q4_k_m.gguf -p "The meaning to life and the universe is" |
| ``` |
| |
| ### Server: |
| ```bash |
| llama-server --hf-repo DesignSoft/TINA_AI3.4_Q4 --hf-file tina_ai3.4-q4_k_m.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. |
| ``` |
| 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 DesignSoft/TINA_AI3.4_Q4 --hf-file tina_ai3.4-q4_k_m.gguf -p "The meaning to life and the universe is" |
| ``` |
| or |
| ``` |
| ./llama-server --hf-repo DesignSoft/TINA_AI3.4_Q4 --hf-file tina_ai3.4-q4_k_m.gguf -c 2048 |
| ``` |
| |