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type: manhattan_precision value: 72.09775967413442 - type: manhattan_recall value: 81.76778564829073 - type: max_ap value: 84.65517268264233 - type: max_f1 value: 76.62890540443034 - type: max_precision value: 72.46526344751685 - type: max_recall value: 81.76778564829073 - type: similarity_accuracy value: 88.10105949470253 - type: similarity_accuracy_threshold value: 68.95147562026978 - type: similarity_ap value: 84.65516103854583 - type: similarity_f1 value: 76.54581123301605 - type: similarity_f1_threshold value: 63.92929553985596 - type: similarity_precision value: 72.46526344751685 - type: similarity_recall value: 81.11333538651063 --- # sheldonrobinson/snowflake-arctic-embed-m-v1.5-Q8_0-GGUF This model was converted to GGUF format from [`Snowflake/snowflake-arctic-embed-m-v1.5`](https://huggingface.co/Snowflake/snowflake-arctic-embed-m-v1.5) 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/Snowflake/snowflake-arctic-embed-m-v1.5) 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 sheldonrobinson/snowflake-arctic-embed-m-v1.5-Q8_0-GGUF --hf-file snowflake-arctic-embed-m-v1.5-q8_0.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo sheldonrobinson/snowflake-arctic-embed-m-v1.5-Q8_0-GGUF --hf-file snowflake-arctic-embed-m-v1.5-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 sheldonrobinson/snowflake-arctic-embed-m-v1.5-Q8_0-GGUF --hf-file snowflake-arctic-embed-m-v1.5-q8_0.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo sheldonrobinson/snowflake-arctic-embed-m-v1.5-Q8_0-GGUF --hf-file snowflake-arctic-embed-m-v1.5-q8_0.gguf -c 2048 ```