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README.md

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+---
+base_model: open-r1/OpenR1-Qwen-7B
+datasets: open-r1/openr1-220k-math
+library_name: transformers
+license: apache-2.0
+model_name: OpenR1-Qwen-7B
+tags:
+- generated_from_trainer
+- trl
+- sft
+- llama-cpp
+licence: license
+---
+
+# tommytracx/OpenR1-Qwen-7B-Q6_K-GGUF
+This model was converted to GGUF format from [`open-r1/OpenR1-Qwen-7B`](https://huggingface.co/open-r1/OpenR1-Qwen-7B) using llama.cpp.
+Refer to the [original model card](https://huggingface.co/open-r1/OpenR1-Qwen-7B) 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 tommytracx/OpenR1-Qwen-7B-Q6_K-GGUF --hf-file openr1-qwen-7b-q6_k.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo tommytracx/OpenR1-Qwen-7B-Q6_K-GGUF --hf-file openr1-qwen-7b-q6_k.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 tommytracx/OpenR1-Qwen-7B-Q6_K-GGUF --hf-file openr1-qwen-7b-q6_k.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./llama-server --hf-repo tommytracx/OpenR1-Qwen-7B-Q6_K-GGUF --hf-file openr1-qwen-7b-q6_k.gguf -c 2048
+```