CLIP ViT-B/32 (OpenAI) β€” xaitalk mirror

This is a bit-identical mirror of the canonical artifact from OpenAI.

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 OpenAI
Upstream (authoritative) https://huggingface.co/openai/clip-vit-base-patch32
Source repo https://github.com/openai/CLIP
Paper https://arxiv.org/abs/2103.00020 (Radford et al. 2021)
License mit (inherited from upstream β€” please respect upstream's terms)
Mirror file pytorch_model.bin
SHA-256 a63082132ba4f97a80bea76823f544493bffa8082296d62d71581a4feff1576f
Size 605,247,071 bytes (577.2 MB)

How xaitalk loads this file

from xaitalk.hub import ensure_model
weights_path = ensure_model("clip-vit-b32")
# 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://arxiv.org/abs/2103.00020 (Radford et al. 2021)
Downloads last month
88
Inference Providers NEW
This model isn't deployed by any Inference Provider. πŸ™‹ Ask for provider support

Collection including xaitalk/clip-vit-b32-mirror

Paper for xaitalk/clip-vit-b32-mirror