yixuan-chia/snowflake-arctic-embed-m-v1.5-Q4_K_M-GGUF
This model was converted to GGUF format from Snowflake/snowflake-arctic-embed-m-v1.5
using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo yixuan-chia/snowflake-arctic-embed-m-v1.5-Q4_K_M-GGUF --hf-file snowflake-arctic-embed-m-v1.5-q4_k_m.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo yixuan-chia/snowflake-arctic-embed-m-v1.5-Q4_K_M-GGUF --hf-file snowflake-arctic-embed-m-v1.5-q4_k_m.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps 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-v1.5-Q4_K_M-GGUF --hf-file snowflake-arctic-embed-m-v1.5-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo yixuan-chia/snowflake-arctic-embed-m-v1.5-Q4_K_M-GGUF --hf-file snowflake-arctic-embed-m-v1.5-q4_k_m.gguf -c 2048
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Model tree for yixuan-chia/snowflake-arctic-embed-m-v1.5-Q4_K_M-GGUF
Base model
Snowflake/snowflake-arctic-embed-m-v1.5Evaluation results
- main_score on MTEB ArguAnatest set self-reported59.530
- map_at_1 on MTEB ArguAnatest set self-reported34.282
- map_at_10 on MTEB ArguAnatest set self-reported50.613
- map_at_100 on MTEB ArguAnatest set self-reported51.269
- map_at_1000 on MTEB ArguAnatest set self-reported51.271
- map_at_20 on MTEB ArguAnatest set self-reported51.158
- map_at_3 on MTEB ArguAnatest set self-reported45.626
- map_at_5 on MTEB ArguAnatest set self-reported48.638
- mrr_at_1 on MTEB ArguAnatest set self-reported34.922
- mrr_at_10 on MTEB ArguAnatest set self-reported50.856