owlvit-base-patch32 safetensors download | Hugging Bay

Q: What is this model?

google/owlvit-base-patch32 is a vision model for zero shot object detection published by google, added to Hugging Bay Jun 29, 2026. Model from Hugging Face for zero shot object detection: google/owlvit-base-patch32 · transformers

Q: Can I use it commercially?

It is released under the apache-2.0 license. Commercial use is allowed. Permissive open license: commercial use, modification, and redistribution are permitted.

Q: How big is it?

Hosted here: 8 files, 1.23 GB. Full repo upstream: 1.23 GB. The recommended download, model.safetensors, is 613 MB.

Q: What can I download here?

Hosted here: 8 files, 1.23 GB. Full repo upstream: 1.23 GB. The original release is at https://huggingface.co/google/owlvit-base-patch32.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 8 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-google-owlvit-base-patch32/safety on Hugging Bay.

Q: Will google/owlvit-base-patch32 run on my computer?

We can’t check the fit; we don’t know your machine. We don’t have your machine’s specs, so no check ran and no verdict is shown. Answer two quick questions and we’ll estimate, from the memory you tell us, whether it fits your machine. Or skip it; you can still download; fit isn’t checked.

google

owlvit-base-patch32

google/owlvit-base-patch32

Model details

zero shot object detectionLicense: apache-2.0SHA-256 recorded for 9 of 10 filessafetensors · BIN

Content controls: not assessed.

Not enough information to say what this model is for or who should use it. Catalog sources: license, cardMetadata.license.

View as JSON →

Your next step

Use it from code

This Python snippet downloads the selected file. Running the model needs its own library and setup.

from urllib.request import urlretrieve

urlretrieve(
    "https://huggingbay.xyz/api/downloads/hf-model-google-owlvit-base-patch32/model.safetensors",
    "model.safetensors",
)

Other ways

Run it on your computerOpen in Hugging Bay appSend to a computerApp links support one GGUF file.

8 hosted of 10 listed · Hashes recorded. Date not recorded.

Selected downloadmodel.safetensors613 MB · 1 file Download · 613 MB (1 file)

Open-file help

Content controls: not assessed.

Check your download →

Compare your file’s SHA-256 with the recorded hash.

8 hosted of 10 listed

Hashes recorded. Date not recorded.

File	Taille	SHA-256	Source	Télécharger
Weights
`model.safetensors` Default	613 MB	`4dbe0399…984ce52b` `4dbe0399f0b7d7c8dddf1535a98769cc30743bebc877aea681998c8d984ce52b`	Hosted	Télécharger
`pytorch_model.bin`	613 MB	`02437334…26d5b531` `02437334ba11db56a312a6c3f0f351f610a1075751bfe36b689636a826d5b531`	Hosted	Télécharger
Tokenizer & config
`config.json`	4.42 KB	`b5934e0d…ff7a9d7c` `b5934e0d2933194b8a85f93674e577feaa1a1ba2dc1d143b2d5e5305ff7a9d7c`	Hosted	Télécharger
`merges.txt`	524.6 KB	`9fd691f7…e299051a` `9fd691f7c8039210e0fced15865466c65820d09b63988b0174bfe25de299051a`	Hosted	Télécharger
`preprocessor_config.json`	392 bytes	`2010d320…f0e9bb6e` `2010d320cd2c68a8bb1de69aaa8f89daf173ef17cc22a30e4baf44b2f0e9bb6e`	Hosted	Télécharger
`special_tokens_map.json`	460 bytes	`f118ab3a…53cdaab6` `f118ab3a983206e4f32583448de6bd6aae4ee21869135cef1f5848a753cdaab6`	Hosted	Télécharger
`tokenizer_config.json`	775 bytes	`da35acee…106bfb6e` `da35aceebeda2adf44094a5867940b09379323b9390fa9197b57044e106bfb6e`	Hosted	Télécharger
`vocab.json`	1.06 MB	—	Upstream only	File metadata
Docs
`.gitattributes`	1.23 KB	`400b270b…cf393ae2` `400b270bc8f5cb44fda65b1a4532ceca0fb452d0637425e861829560cf393ae2`	Upstream only	File metadata
`README.md`	5.15 KB	`a16c7074…25f236bf` `a16c707494da894773e85c1be976ae605a7b3a3ce92cf9ed277623dd25f236bf`	Hosted	Télécharger

Vérifier un téléchargement

In the folder where you saved model.safetensors, run:

macOS

shasum -a 256 -- 'model.safetensors'

Linux

sha256sum -- 'model.safetensors'

Windows

Get-FileHash -LiteralPath 'model.safetensors' -Algorithm SHA256

Compare the result with the recorded SHA-256.

owlvit-base-patch32

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