How to use from the
Use from the
Model2Vec library
from model2vec import StaticModel

model = StaticModel.from_pretrained("777Radik/potion-multilingual-128M-int8")

777Radik/potion-multilingual-128M-int8

int8 + PCA-reduced (256→128) quantization of minishlab/potion-multilingual-128M, for in-browser static embeddings (model2vec / model2vec-rs WASM). ~64 MB.

  • Compression: FP32 → Int8; embedding dim 256 → 128 (PCA). Full multilingual vocabulary kept (incl. Cyrillic) — no script stripping.
  • Format: model2vec safetensors — loadable by model2vec (Python), model2vec-rs (Rust), and in the browser via WASM from_bytes.
  • Inference: tokenize → token-vector lookup → mean-pool → L2-normalize → cosine.
from model2vec import StaticModel
m = StaticModel.from_pretrained("777Radik/potion-multilingual-128M-int8")
emb = m.encode(["пример текста", "example text"])

Produced by scripts/quantize-potion.py --dim 128.

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