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.gitattributes

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+snowflake-arctic-embed-m-F16.gguf filter=lfs diff=lfs merge=lfs -text
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README.md

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+# yixuan-chia/snowflake-arctic-embed-m-GGUF
+This model was converted to GGUF format from [`Snowflake/snowflake-arctic-embed-m`](https://huggingface.co/Snowflake/snowflake-arctic-embed-m) using llama.cpp.
+Refer to the [original model card](https://huggingface.co/Snowflake/snowflake-arctic-embed-m) 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 yixuan-chia/snowflake-arctic-embed-m-GGUF --hf-file snowflake-arctic-embed-m-q8_0.gguf -p "The meaning to life and the universe is"
+```
+### Server:
+```bash
+llama-server --hf-repo yixuan-chia/snowflake-arctic-embed-m-GGUF --hf-file snowflake-arctic-embed-m-q8_0.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 yixuan-chia/snowflake-arctic-embed-m-GGUF --hf-file snowflake-arctic-embed-m-q8_0.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./llama-server --hf-repo yixuan-chia/snowflake-arctic-embed-m-GGUF --hf-file snowflake-arctic-embed-m-q8_0.gguf -c 2048
+```

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