IgBert safetensors download (1.68 GB) | Hugging Bay

Q: What is this model?

Exscientia/IgBert is an open-weights language model for masked-language modeling published by Exscientia, added to Hugging Bay Jun 29, 2026. Model from Hugging Face for fill mask: Exscientia/IgBert · transformers

Q: Can I use it commercially?

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

Q: How big is it?

Hosted here: at least 7 listed files; full count and size unknown. Full repo upstream: 1.68 GB. The recommended download, model.safetensors, is 1.68 GB.

Q: What can I download here?

Hosted here: at least 7 listed files; full count and size unknown. Full repo upstream: 1.68 GB. The original release is at https://huggingface.co/Exscientia/IgBert.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 7 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-exscientia-igbert/safety on Hugging Bay.

Q: Will Exscientia/IgBert 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.

Exscientia

IgBert

Exscientia/IgBert

Model details

masked-language modelingLicense: mitSHA-256 recorded for 7 of 8 filessafetensors

Content controls: not assessed.

Listed for predicting masked text; for developers working with masked language models. Catalog sources: license, cardMetadata.license, baseModel, task, cardMetadata.pipelineTag.

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-exscientia-igbert/model.safetensors",
    "model.safetensors",
)

Other ways

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

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

Selected downloadmodel.safetensors1.68 GB · 1 file Download · 1.68 GB (1 file)

Open-file help

Content controls: not assessed.

Check your download →

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

7 hosted of 8 listed

Hashes recorded. Date not recorded.

File	Größe	SHA-256	Quelle	Herunterladen
Weights
`model.safetensors` Default	1.68 GB	`e9bdc24c…99db7740` `e9bdc24c7a50bb303b75f8292eca8d47ddac39f00ef9802972ded38899db7740`	Hosted	Herunterladen
Tokenizer & config
`config.json`	686 bytes	`ca556768…d57ec6b4` `ca556768db0110154280954140f7b72293d1176a89559ed60edf27a9d57ec6b4`	Hosted	Herunterladen
`generation_config.json`	90 bytes	`77f3ed0b…6732212a` `77f3ed0bb710ae4a3456a726c6bb90fee253f9fb666b6824eb6552e06732212a`	Hosted	Herunterladen
`tokenizer_config.json`	1.29 KB	`e9ba0a56…2c8afb78` `e9ba0a565495ee106a065bb9460e6d5ed7ba57f2c4f35eae33da961f2c8afb78`	Hosted	Herunterladen
`vocab.txt`	81 bytes	`7ea18f4f…a3a30607` `7ea18f4fe3a796c1146f9830d50334a251f368db96bdd0606e78846ca3a30607`	Hosted	Herunterladen
`special_tokens_map.json`	125 bytes	`b6d346be…76237ee3` `b6d346be366a7d1d48332dbc9fdf3bf8960b5d879522b7799ddba59e76237ee3`	Hosted	Herunterladen
Docs
`.gitattributes`	1.52 KB	—	Upstream only	File metadata
`README.md`	3.15 KB	`e765306d…5c175924` `e765306db3ee86fa67b503ac9f30cebf262ffd5f9e6399324921c02d5c175924`	Hosted	Herunterladen

Einen Download prüfen

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.

IgBert

Einen Download prüfen

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