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.gitattributes

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README.md

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----
-license: llama2
-base_model: WizardLMTeam/WizardLM-13B-V1.2
-tags:
-- llama-cpp
-- gguf-my-repo
----
-
-# tsqn/WizardLM-13B-V1.2-Q4_K_M-GGUF
-This model was converted to GGUF format from [`WizardLMTeam/WizardLM-13B-V1.2`](https://huggingface.co/WizardLMTeam/WizardLM-13B-V1.2) 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/WizardLMTeam/WizardLM-13B-V1.2) 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 tsqn/WizardLM-13B-V1.2-Q4_K_M-GGUF --hf-file wizardlm-13b-v1.2-q4_k_m.gguf -p "The meaning to life and the universe is"
-```
-
-### Server:
-```bash
-llama-server --hf-repo tsqn/WizardLM-13B-V1.2-Q4_K_M-GGUF --hf-file wizardlm-13b-v1.2-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 tsqn/WizardLM-13B-V1.2-Q4_K_M-GGUF --hf-file wizardlm-13b-v1.2-q4_k_m.gguf -p "The meaning to life and the universe is"
-```
-or 
-```
-./llama-server --hf-repo tsqn/WizardLM-13B-V1.2-Q4_K_M-GGUF --hf-file wizardlm-13b-v1.2-q4_k_m.gguf -c 2048
-```
+---
+license: llama2
+base_model: WizardLMTeam/WizardLM-13B-V1.2
+tags:
+- llama-cpp
+- gguf-my-repo
+---
+
+# tsqn/WizardLM-13B-V1.2-Q4_K_M-GGUF
+This model was converted to GGUF format from [`WizardLMTeam/WizardLM-13B-V1.2`](https://huggingface.co/WizardLMTeam/WizardLM-13B-V1.2) 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/WizardLMTeam/WizardLM-13B-V1.2) 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 tsqn/WizardLM-13B-V1.2-Q4_K_M-GGUF --hf-file wizardlm-13b-v1.2-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo tsqn/WizardLM-13B-V1.2-Q4_K_M-GGUF --hf-file wizardlm-13b-v1.2-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 tsqn/WizardLM-13B-V1.2-Q4_K_M-GGUF --hf-file wizardlm-13b-v1.2-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./llama-server --hf-repo tsqn/WizardLM-13B-V1.2-Q4_K_M-GGUF --hf-file wizardlm-13b-v1.2-q4_k_m.gguf -c 2048
+```

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