kernel: 7.3.0-10-generic
python: Python 3.14.8
torch: 2.15.0+cpu
sentence-transformers: 6.2.0
transformers: 5.22.1
onnxruntime: 1.31.1
numpy: 2.5.4
sqlite (python3 stdlib): 3.53.4
pytrec-eval-terrier: 0.5.11
sqlite-vec (pip): 0.1.9
xerj: xerj v1.0.0-rc.101
xerj tarball sha256: 999647a588cb113b49ec27cb72c43afa6bf367d8fb2b079b510eee703b025800 (xerj-1.0.0-rc.101-x86_64-unknown-linux-gnu.tar.gz, sha256sum -c OK)
bge-small-en-v1.5 HF snapshot: 5c38ec7c405ec4b44b94cc5a9bb96e735b38267a
embeddinggemma ONNX: onnx-community/embeddinggemma-300m-ONNX rev=5090578d9565bb06545b4552f76e6bc2c93e4a66, onnx/model.onnx_data sha256 ef835ae565d8695236652475903078e8ed794c7c35faf1164d78ec3238e8a88d
datasets (BEIR zips, https://public.ukp.informatik.tu-darmstadt.de/thakur/BEIR/datasets/): scifact.zip 536e14446a0ba56ed1398ab1055f39fe852686ecad24a6306c80c490fa8e0165, nfcorpus.zip efe5be03f8c5b86a5870102d0599d227c8c6e2484328e68c6522560385671b0b, fiqa.zip 32c7df99ed21252fdfb2cf3f5673502a8d245ee0c44c4a133570d92ce2b3ad02
CPU(s):                                  32
Model name:                              AMD RYZEN AI MAX+ 395 w/ Radeon 8060S
Thread(s) per core:                      2
Core(s) per socket:                      16
Socket(s):                               1
CPU(s) scaling MHz:                      66%
CPU max MHz:                             5187.5000
L3 cache:                                64 MiB (2 instances)
               total        used        free      shared  buff/cache   available
Mem:             119          14          40           2          69         105
