Clip Vit B32 Mirror

--- license: mit tags: - mirror - xai - multimodal - clip - zero-shot-image-classification --- # CLIP ViT-B/32 (OpenAI) — 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](https://github.com/xaitalk/xaitalk) library — 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 — 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 ```python 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) ```

Source context: 30 downloads · 0 likes · Pipeline zero-shot-image-classification · Repo xaitalk/clip-vit-b32-mirror