Update README.md

README.md

@@ -9,51 +9,6 @@ tags:
 - llama-3
 - pytorch
 - llama-cpp
-- gguf-my-repo
 base_model: nvidia/Llama3-ChatQA-1.5-8B
 pipeline_tag: text-generation
----
-
-# narainp/Llama3-ChatQA-1.5-8B-Q4_K_M-GGUF
-This model was converted to GGUF format from [`nvidia/Llama3-ChatQA-1.5-8B`](https://huggingface.co/nvidia/Llama3-ChatQA-1.5-8B) 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/nvidia/Llama3-ChatQA-1.5-8B) 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 --hf-repo narainp/Llama3-ChatQA-1.5-8B-Q4_K_M-GGUF --hf-file llama3-chatqa-1.5-8b-q4_k_m.gguf -p "The meaning to life and the universe is"
-```
-
-### Server:
-```bash
-llama-server --hf-repo narainp/Llama3-ChatQA-1.5-8B-Q4_K_M-GGUF --hf-file llama3-chatqa-1.5-8b-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.
-```
-./main --hf-repo narainp/Llama3-ChatQA-1.5-8B-Q4_K_M-GGUF --hf-file llama3-chatqa-1.5-8b-q4_k_m.gguf -p "The meaning to life and the universe is"
-```
-or 
-```
-./server --hf-repo narainp/Llama3-ChatQA-1.5-8B-Q4_K_M-GGUF --hf-file llama3-chatqa-1.5-8b-q4_k_m.gguf -c 2048
-```
+---