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README.md

@@ -1,15 +1,16 @@
 ---
+base_model: HuggingFaceH4/zephyr-7b-beta
+datasets:
+- HuggingFaceH4/ultrachat_200k
+- HuggingFaceH4/ultrafeedback_binarized
 language:
 - en
 license: mit
+pipeline_tag: text-generation
 tags:
 - generated_from_trainer
 - llama-cpp
 - gguf-my-repo
-base_model: mistralai/Mistral-7B-v0.1
-datasets:
-- HuggingFaceH4/ultrachat_200k
-- HuggingFaceH4/ultrafeedback_binarized
 widget:
 - example_title: Pirate!
   messages:
@@ -24,7 +25,6 @@ widget:
       treat. Once he's gone, ye can clean up yer lawn and enjoy the peace and quiet
       once again. But beware, me hearty, for there may be more llamas where that one
       came from! Arr!
-pipeline_tag: text-generation
 model-index:
 - name: zephyr-7b-beta
   results:
@@ -173,29 +173,43 @@ model-index:
 # newsletter/zephyr-7b-beta-Q6_K-GGUF
 This model was converted to GGUF format from [`HuggingFaceH4/zephyr-7b-beta`](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) 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/HuggingFaceH4/zephyr-7b-beta) for more details on the model.
-## Use with llama.cpp
 
-Install llama.cpp through brew.
+## Use with llama.cpp
+Install llama.cpp through brew (works on Mac and Linux)
 
 ```bash
-brew install ggerganov/ggerganov/llama.cpp
+brew install llama.cpp
+
 ```
 Invoke the llama.cpp server or the CLI.
 
-CLI:
-
+### CLI:
 ```bash
-llama-cli --hf-repo newsletter/zephyr-7b-beta-Q6_K-GGUF --model zephyr-7b-beta.Q6_K.gguf -p "The meaning to life and the universe is"
+llama-cli --hf-repo newsletter/zephyr-7b-beta-Q6_K-GGUF --hf-file zephyr-7b-beta-q6_k.gguf -p "The meaning to life and the universe is"
 ```
 
-Server:
-
+### Server:
 ```bash
-llama-server --hf-repo newsletter/zephyr-7b-beta-Q6_K-GGUF --model zephyr-7b-beta.Q6_K.gguf -c 2048
+llama-server --hf-repo newsletter/zephyr-7b-beta-Q6_K-GGUF --hf-file zephyr-7b-beta-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 newsletter/zephyr-7b-beta-Q6_K-GGUF --hf-file zephyr-7b-beta-q6_k.gguf -p "The meaning to life and the universe is"
+```
+or 
 ```
-git clone https://github.com/ggerganov/llama.cpp &&             cd llama.cpp &&             make &&             ./main -m zephyr-7b-beta.Q6_K.gguf -n 128
+./llama-server --hf-repo newsletter/zephyr-7b-beta-Q6_K-GGUF --hf-file zephyr-7b-beta-q6_k.gguf -c 2048
 ```