gbert-base safetensors download (442 MB) | Hugging Bay

Q: What is this model?

deepset/gbert-base is an open-weights language model for masked-language modeling published by deepset, added to Hugging Bay Jun 29, 2026. Model from Hugging Face: deepset/gbert-base

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: 8 files, 1.42 GB. Full repo upstream: 1.42 GB. The recommended download, model.safetensors, is 442.2 MB.

Q: What can I download here?

Hosted here: 8 files, 1.42 GB. Full repo upstream: 1.42 GB. The original release is at https://huggingface.co/deepset/gbert-base.

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-deepset-gbert-base/safety on Hugging Bay.

Q: Will deepset/gbert-base 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.

deepset

gbert-base

deepset/gbert-base

Model details

masked-language modelingLicense: mitHashes recordedsafetensors · BIN · H5

Content controls: not assessed.

Model from Hugging Face: deepset/gbert-base

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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-deepset-gbert-base/model.safetensors",
    "model.safetensors",
)

Other ways

8 hosted of 9 listed · Hashes recorded. Date not recorded.

Selected downloadmodel.safetensors442 MB · 1 file Download · 442 MB (1 file)

Open-file help

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Signed by the harbor

8 hosted of 9 listed

Hashes recorded. Date not recorded.

File	Größe	SHA-256	Quelle	Herunterladen
Weights
`model.safetensors` Default	442.2 MB	`1c3d31aa…132461fe` `1c3d31aa6461261d8714a4ba57033437dba5afce502be1faaa068368132461fe`	Hosted	Herunterladen
`pytorch_model.bin`	442.3 MB	`227220a5…cea87867` `227220a5807266f9120d332a562ad169c95411c54ee0f2439955fe5dcea87867`	Hosted	Herunterladen
Tokenizer & config
`config.json`	362 bytes	`477098ee…736a1bbf` `477098ee1a14b26b8d196d8fb8aebfb5fdf1b44bdff3286a4e10abf8736a1bbf`	Hosted	Herunterladen
`tf_model.h5`	539.6 MB	`44ec20c0…f9da340a` `44ec20c0fb507650d3f8f7d68550535696945d5fed0d8dc781079a67f9da340a`	Hosted	Herunterladen
`tokenizer_config.json`	83 bytes	`25f2b98f…dca10378` `25f2b98fcd4c39add7f30fa8e129c9d7d1fc2d27a37d615ae6452a47dca10378`	Hosted	Herunterladen
`vocab.txt`	239.8 KB	`bf186f7f…f13039a3` `bf186f7fb9cb667d811c08b45ce64d1e8e262277bb053f05d1aef3e9f13039a3`	Hosted	Herunterladen
Docs
`.gitattributes`	399 bytes	`a368a21c…5ccc6f59` `a368a21c472071feec9095f63d5f7d3433826c1c476a6995f072b6755ccc6f59`	Upstream only	File metadata
`README.md`	2.9 KB	`7dd66a45…92548118` `7dd66a45e488b471e8808c51b1101b7aa45bab54151b7eb265cfd56992548118`	Hosted	Herunterladen
`license.txt`	1.05 KB	`3e6d3306…7a1cd5a2` `3e6d33063d766183a848ffabfabf0ec945be81bd9f7eb230d0f69ceb7a1cd5a2`	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.

gbert-base

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