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1from chessnets.pipelines.lc0 import Lc0Pipeline
2
3pipeline = Lc0Pipeline.from_pretrained("shermansiu/lc0_t82-768x15x24h-swa-7364000")
4predictions = pipeline("1. e4 e5")config.json: canonical, fully materialized ChessNets architecture configmodel.safetensors: decoded float32 PyTorch tensorsprovenance.json: source and conversion hashesoriginal/model.pb.gz: original Lc0 protobuf checkpointtraining/original_lczero_training_config.yaml: original training configLINEAR16 encoding. Conversion decoded
those values into float32 tensors; it cannot restore precision already lost in
the source encoding.