--- base_model: Qwen/Qwen2-72B-Instruct library_name: transformers license: other tags: - llama-cpp - Qwen - Qwen2-72B-Instruct - Qwen2-72B - GGUF datasets: hawky_fb_bidding_prompts --- # Sri-Vigneshwar-DJ/sarvam-2b-v0.5-GGUF This model was converted to GGUF format from [`Qwen/Qwen2-72B-Instruct`](https://huggingface.co/Qwen/Qwen2-72B-Instruct) using llama.cpp Refer to the [original model card](https://huggingface.co/Qwen/Qwen2-72B-Instruct) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) from https://github.com/ggerganov/llama.cpp.git ```bash brew install llama.cpp or !git clone https://github.com/ggerganov/llama.cpp.git ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash ! /content/llama.cpp/llama-cli -m ./sarvam-2b-v0.5-GGUF -n 90 --repeat_penalty 1.0 --color -i -r "User:" -f /content/llama.cpp/prompts/chat-with-bob.txt or llama-cli --hf-repo Sri-Vigneshwar-DJ/hawky-ai-Qwen2-Math-72B-Instruct-GGUF --hf-file FP8.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo Sri-Vigneshwar-DJ/sarvam-2b-v0.5-GGUF --hf-file FP8.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 or ''!make GGML_OPENBLAS=1' along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make or !make GGML_OPENBLAS=1 ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo Sri-Vigneshwar-DJ/hawky-ai-Qwen2-Math-72B-Instruct-GGUF --hf-file FP8.gguf -p "FB_POST {poster} = ~Price?, Just give the upper and lower bound" ``` or ``` ./llama-server --hf-repo Sri-Vigneshwar-DJ/hawky-ai-Qwen2-Math-72B-Instruct-GGUF --hf-file sFP8.gguf -c 2048 ```