bert-base-multilingual-uncased download | Hugging Bay

Q: What is this model?

google-bert/bert-base-multilingual-uncased is an open-weights language model for masked-language modeling published by google-bert, added to Hugging Bay Jun 29, 2026. Model from Hugging Face for fill mask: google-bert/bert-base-multilingual-uncased · 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: at least 9 listed files; full count and size unknown. Full repo upstream: 3.02 GB. The recommended download, model.safetensors, is 672.2 MB.

Q: What can I download here?

Hosted here: at least 9 listed files; full count and size unknown. Full repo upstream: 3.02 GB. The original release is at https://huggingface.co/google-bert/bert-base-multilingual-uncased.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 9 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-google-bert-bert-base-multilingual-uncased/safety on Hugging Bay.

Q: Will google-bert/bert-base-multilingual-uncased 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-bert

bert-base-multilingual-uncased

Can I run bert-base-multilingual-uncased on my computer?

It depends on your memory, processor, file format and runtime. Hugging Bay offers 9 hosted files; check the file list for the exact selection. A file-size fit is an estimate, not a successful run or speed promise. Read the license before use.

bert-base-multilingual-uncased is an open-weights language model for masked-language modeling. Model weights are learned parameters; a runtime loads them. A hosted file is an individual file Hugging Bay can serve. SHA-256 identifies exact file bytes. The availability date above applies to this file record, not the upstream metadata update date.

As of the recorded file availability check on 2026-10-22.

Recorded SHA-256 for model.safetensors: b33adb2b700b7029a64a4a14ddec6bda8555d2ca879e80a75789fd9542a6290e. Exact file evidence · Machine-readable source facts · Run evidence and any recorded receipts. A checksum fingerprints only the named file bytes; it does not prove safety, quality, a complete multi-file selection or a successful run.

Updated 2026-10-21 · Page-copy source revision 8871bab84e1cf80aea1686a944ec335078a6c036 · Source files: apps/web/lib/model-page-template.mjs, apps/web/lib/model-page-v3.mjs, apps/web/lib/aeo-page.mjs · Full revision record

Model metadata: As of 2024-02-19 at the model source. Popularity counters are source-reported, not measured by Hugging Bay. Availability checked 2026-10-22.

google-bert/bert-base-multilingual-uncased

Model details

masked-language modelingLicense: apache-2.0Hashes recordedsafetensors · BIN · H5

Content controls: not assessed.

The catalog lists this model for filling in missing words in text. Catalog sources: license, cardMetadata.license, task, cardMetadata.pipelineTag.

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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-bert-bert-base-multilingual-uncased/model.safetensors",
    "model.safetensors",
)

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

Selected downloadmodel.safetensors672 MB · 1 file Download · 672 MB (1 file)

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Check your download →

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

9 hosted of 10 listed

Hashes recorded. Date not recorded.

File	Taille	SHA-256	Source	Télécharger
Weights
`model.safetensors` Default	672.2 MB	`b33adb2b…42a6290e` `b33adb2b700b7029a64a4a14ddec6bda8555d2ca879e80a75789fd9542a6290e`	Hosted	Télécharger
`pytorch_model.bin`	672.3 MB	`2fec0e2a…2a320e8d` `2fec0e2a13cde5fa386fa00ba3e1bfea14b5d8fd8760f37f051799812a320e8d`	Hosted	Télécharger
Tokenizer & config
`config.json`	625 bytes	`fba5d4b0…8f18db1c` `fba5d4b0a351a43f6ccb7a6587301fd9f6876ca36aae62af762af67c8f18db1c`	Hosted	Télécharger
`flax_model.msgpack`	669.9 MB	`f710cb05…e9682237` `f710cb055884fa24672430f027b5375f0651dda1d9011f7d2407bc58e9682237`	Hosted	Télécharger
`tf_model.h5`	999.4 MB	`77d2ed6e…ccd83921` `77d2ed6e37792d0e3224dddf5d4b509c65d0e9fb131b97339598b852ccd83921`	Hosted	Télécharger
`tokenizer.json`	1.72 MB	`41a9e8cc…21faa21b` `41a9e8ccfd02a7bf5bb8426ed22eec3a5bd81d85d7c10ef4a5cbdbfa21faa21b`	Hosted	Télécharger
`tokenizer_config.json`	48 bytes	`a025160e…d214bf10` `a025160ef0431f1a392f6f050c1310f4c5d9fb6f275932dbccba73c4d214bf10`	Hosted	Télécharger
`vocab.txt`	871.9 KB	`87b44292…4228ef3f` `87b44292b452f6c05afa49b2e488e7eedf79ea4f4c39db6f2f4b37764228ef3f`	Hosted	Télécharger
Docs
`.gitattributes`	445 bytes	`98c91dab…927304c1` `98c91dabef4df27b2fc7c8454d220aba47476f73593cbd034d961fe4927304c1`	Upstream only	File metadata
`README.md`	8.93 KB	`d83fc68b…18c7b17f` `d83fc68b59583ff10472ff7b9c3ed1c0c0f07ccd09aeb5a38b97af6c18c7b17f`	Hosted	Télécharger

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bert-base-multilingual-uncased

Can I run bert-base-multilingual-uncased on my computer?

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