Sri-Vigneshwar-DJ
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README.md
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---
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base_model: Qwen/Qwen2-72B-Instruct
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library_name: transformers
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license: other
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tags:
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- llama-cpp
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- Qwen
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- Qwen2-72B-Instruct
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- Qwen2-72B
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- GGUF
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datasets: hawky_fb_bidding_prompts
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---
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# Sri-Vigneshwar-DJ/sarvam-2b-v0.5-GGUF
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This model was converted to GGUF format from [`Qwen/Qwen2-72B-Instruct`](https://huggingface.co/Qwen/Qwen2-72B-Instruct) using llama.cpp
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Refer to the [original model card](https://huggingface.co/Qwen/Qwen2-72B-Instruct) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux) from []
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```bash
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brew install llama.cpp or !git clone https://github.com/ggerganov/llama.cpp.git
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```
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Invoke the llama.cpp server or the CLI.
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### CLI:
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```bash
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! /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
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or
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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"
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```
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### Server:
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```bash
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llama-server --hf-repo Sri-Vigneshwar-DJ/sarvam-2b-v0.5-GGUF --hf-file FP8.gguf -c 2048
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```
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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.
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Step 1: Clone llama.cpp from GitHub.
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```
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git clone https://github.com/ggerganov/llama.cpp
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```
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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).
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```
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cd llama.cpp && LLAMA_CURL=1 make
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or
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!make GGML_OPENBLAS=1
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```
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Step 3: Run inference through the main binary.
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```
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./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"
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```
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or
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```
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./llama-server --hf-repo Sri-Vigneshwar-DJ/hawky-ai-Qwen2-Math-72B-Instruct-GGUF --hf-file sFP8.gguf -c 2048
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```
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