ESM-2 t6 8M (Meta FAIR) β€” 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 β€” 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_t6_8M_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 β€” please respect upstream's terms)
Mirror file pytorch_model.bin
SHA-256 9edcf393212f3a26684cd68ca8095ec43c2c341ee0fcc3ba7a4d3a47c5dc138f
Size 31,406,877 bytes (30.0 MB)

How xaitalk loads this file

from xaitalk.hub import ensure_model
weights_path = ensure_model("esm2-t6-8m-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)
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