embeddings
This is a repo created to keep a collection of quantized bert models in ggml format.
usage
You can utilize bert.cpp as usual or use our new api to quickly prototype on real use-case scenarios for text similarity.
embeddings sample
./main -m small -p "word"
// [0.0698, -0.0024, -0.0153, 0.0193, -0.1060, -0.0278, 0.1424, -0.0056, -0.0536...
api reference
api | size |
---|---|
nano | 11.2 |
small | 14.5 |
medium | 21.3 |
large | 68.8 |
We are planning to update the list to always support the lastest open-source models on the repo and api.
As of 02/20/2024 large model outpus are highly biased towards positive numbers, we are still researching why, nano, small and medium models are working as expected.
api sample
// semantic relationship between "I love this" and "I hate this"
nano: 0.4614074121704735
small: 0.6553150807627873
medium: 0.8263292187144999
large: 0.8567815005348627
Note: the api is only for prototyping as of now, we are currently working on scaling things up soon.
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