Update README.md

README.md

@@ -15,7 +15,24 @@ tags:
 This model was converted to GGUF format from [`GoToCompany/llama3-8b-cpt-sahabatai-v1-instruct`](https://huggingface.co/GoToCompany/llama3-8b-cpt-sahabatai-v1-instruct) 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/GoToCompany/llama3-8b-cpt-sahabatai-v1-instruct) for more details on the model.
 
-## Use with llama.cpp
+## Run with Ollama
+Install Ollama
+
+```bash
+curl -fsSL https://ollama.com/install.sh | sh
+```
+
+### Run Service:
+```bash
+ollama serve
+```
+
+### Run in CLI:
+```bash
+ollama run hf.co/ojiset22/llama3-8b-cpt-sahabatai-v1-instruct-Q4_K_M-GGUF
+```
+
+## Run with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)
 
 ```bash
@@ -33,24 +50,3 @@ llama-cli --hf-repo ojiset22/llama3-8b-cpt-sahabatai-v1-instruct-Q4_K_M-GGUF --h
 ```bash
 llama-server --hf-repo ojiset22/llama3-8b-cpt-sahabatai-v1-instruct-Q4_K_M-GGUF --hf-file llama3-8b-cpt-sahabatai-v1-instruct-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 ojiset22/llama3-8b-cpt-sahabatai-v1-instruct-Q4_K_M-GGUF --hf-file llama3-8b-cpt-sahabatai-v1-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
-```
-or 
-```
-./llama-server --hf-repo ojiset22/llama3-8b-cpt-sahabatai-v1-instruct-Q4_K_M-GGUF --hf-file llama3-8b-cpt-sahabatai-v1-instruct-q4_k_m.gguf -c 2048
-```