Plasmoxy/bge-micro-v2-Q4_K_M-GGUF
Really small BGE embedding model but with 4-bit gguf quant.
This model was converted to GGUF format from TaylorAI/bge-micro-v2
using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
!!! IMPORTANT !!! - context size is 512, specify the context size (-c 512) for llama cpp.
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 Plasmoxy/bge-micro-v2-Q4_K_M-GGUF --hf-file bge-micro-v2-q4_k_m.gguf -c 512 -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Plasmoxy/bge-micro-v2-Q4_K_M-GGUF --hf-file bge-micro-v2-q4_k_m.gguf -c 512
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 Plasmoxy/bge-micro-v2-Q4_K_M-GGUF --hf-file bge-micro-v2-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo Plasmoxy/bge-micro-v2-Q4_K_M-GGUF --hf-file bge-micro-v2-q4_k_m.gguf -c 2048
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Model tree for Plasmoxy/bge-micro-v2-Q4_K_M-GGUF
Base model
TaylorAI/bge-micro-v2Evaluation results
- accuracy on MTEB AmazonCounterfactualClassification (en)test set self-reported67.761
- ap on MTEB AmazonCounterfactualClassification (en)test set self-reported29.638
- f1 on MTEB AmazonCounterfactualClassification (en)test set self-reported61.312
- accuracy on MTEB AmazonPolarityClassificationtest set self-reported79.755
- ap on MTEB AmazonPolarityClassificationtest set self-reported74.214
- f1 on MTEB AmazonPolarityClassificationtest set self-reported79.653
- accuracy on MTEB AmazonReviewsClassification (en)test set self-reported37.452
- f1 on MTEB AmazonReviewsClassification (en)test set self-reported37.025
- map_at_1 on MTEB ArguAnatest set self-reported31.152
- map_at_10 on MTEB ArguAnatest set self-reported46.702