albert-base-v2 safetensors download (47 MB) | Hugging Bay

Q: What is this model?

albert/albert-base-v2 is an open-weights language model for masked-language modeling published by albert, added to Hugging Bay Jun 29, 2026. Model from Hugging Face for fill mask: albert/albert-base-v2 · 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: 10 files, 267.5 MB. Full repo upstream: 330.6 MB. The recommended download, model.safetensors, is 47.4 MB.

Q: What can I download here?

Hosted here: 10 files, 267.5 MB. Full repo upstream: 330.6 MB. The original release is at https://huggingface.co/albert/albert-base-v2.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 10 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-albert-albert-base-v2/safety on Hugging Bay.

Q: Will albert/albert-base-v2 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.

albert

albert-base-v2

albert/albert-base-v2

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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from urllib.request import urlretrieve

urlretrieve(
    "https://huggingbay.xyz/api/downloads/hf-model-albert-albert-base-v2/model.safetensors",
    "model.safetensors",
)

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10 hosted of 12 listed · Hashes recorded. Date not recorded.

Selected downloadmodel.safetensors47 MB · 1 file Download · 47 MB (1 file)

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Check your download →

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

10 hosted of 12 listed

Hashes recorded. Date not recorded.

File	Tamanho	SHA-256	Origem	Baixar
Weights
`model.safetensors` Default	47.4 MB	`d24c30ec…73ae33eb` `d24c30ec641e40087eed68adf958afe2dab0432790ec3ffa88b31ce773ae33eb`	Hosted	Baixar
`pytorch_model.bin`	47.4 MB	`46704a4f…df070299` `46704a4f59d6665d1f0c4fe5cda17dd6308beead11193d7572641166df070299`	Hosted	Baixar
Tokenizer & config
`config.json`	684 bytes	`f5b7ef28…9351dc03` `f5b7ef285a15ebbc7043b23284e60ac6f6de8d0a6051e282dfdf81da9351dc03`	Hosted	Baixar
`flax_model.msgpack`	44.9 MB	`40dc942f…a4faacc7` `40dc942fcc79e8e88956b39eb097f1a116e7b492c80fc4d5b817c973a4faacc7`	Hosted	Baixar
`rust_model.ot`	62.7 MB	`3b207f0b…4c11cdfd` `3b207f0b36b2d7b7388456ee42f8c469dd842939b1933003ba560ccc4c11cdfd`	Hosted	Baixar
`spiece.model`	760.3 KB	`fefb02b6…a02d0336` `fefb02b667a6c5c2fe27602d28e5fb3428f66ab89c7d6f388e7c8d44a02d0336`	Hosted	Baixar
`tf_model.h5`	63 MB	`d894ce4d…c2f71211` `d894ce4dc1051893a3c41f4ea1a9a50fca7b977086e7f28eb0525c45c2f71211`	Hosted	Baixar
`tokenizer.json`	1.31 MB	`6e2aa3d5…ec4d2ac3` `6e2aa3d5ca4c6841bc36a5028179cb4d63c129931fa18fce38fdb38cec4d2ac3`	Hosted	Baixar
`tokenizer_config.json`	25 bytes	`994f4675…aecd18ce` `994f46754c5bf4014f1aa92d34b1374319c3a6b3f702105cd5b742beaecd18ce`	Hosted	Baixar
`with-prefix-tf_model.h5`	63 MB	`d894ce4d…c2f71211` `d894ce4dc1051893a3c41f4ea1a9a50fca7b977086e7f28eb0525c45c2f71211`	Upstream only	File metadata
Docs
`.gitattributes`	445 bytes	`98c91dab…927304c1` `98c91dabef4df27b2fc7c8454d220aba47476f73593cbd034d961fe4927304c1`	Upstream only	File metadata
`README.md`	9.75 KB	`aa29d371…56502772` `aa29d37125110a1dcec4a91f33efb33c5102bca6052ac70cfd9d63e056502772`	Hosted	Baixar

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albert-base-v2

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