xaitalk/esm2-t33-650m-pt-mirror

ESM-2 t33 650M (Meta FAIR) — xaitalk mirror

This is a bit-identical mirror of the canonical artifact from Meta AI / FAIR.

The mirror exists only as a resilience fallback for the xaitalk library — the upstream remains authoritative. All credit and licensing for the model belong to the original authors.

Attribution

Field	Value
Original authors	Meta AI / FAIR
Upstream (authoritative)	https://huggingface.co/facebook/esm2_t33_650M_UR50D
Source repo	https://github.com/facebookresearch/esm
Paper	https://www.science.org/doi/10.1126/science.ade2574 (Lin et al. 2022)
License	mit (inherited from upstream — please respect upstream's terms)
Mirror file	pytorch_model.bin
SHA-256	c874668852c7275a159e2c7ceb6069671d7b1ba2c7b52f59600b34ce0f721008
Size	2,609,621,831 bytes (2488.7 MB)

How xaitalk loads this file

from xaitalk.hub import ensure_model
weights_path = ensure_model("esm2-t33-650m-pt")
# Tries the canonical upstream first; falls back to this xaitalk mirror
# automatically if upstream is unreachable.

Why mirror?

xaitalk's research-grade reproducibility claim relies on every weight file being recoverable years from now. We mirror artifacts ≤ 2.5 GB under xaitalk/*-mirror so the pipeline survives upstream URL changes, repo renames, or deletions. Bit-level parity with the canonical is asserted in CI via python -m xaitalk.hub verify-mirrors.

Citation

If you use this model, please cite the original paper (not the mirror):

https://www.science.org/doi/10.1126/science.ade2574 (Lin et al. 2022)