HoogBERTa safetensors download (575 MB) | Hugging Bay

Q: What is this model?

lst-nectec/HoogBERTa is an open-weights language model for masked-language modeling published by lst-nectec, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for fill mask: lst-nectec/HoogBERTa · 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: 5 files, 578 MB. Full repo upstream: 1.15 GB. The recommended download, model.safetensors, is 574.6 MB.

Q: What can I download here?

Hosted here: 5 files, 578 MB. Full repo upstream: 1.15 GB. The original release is at https://huggingface.co/lst-nectec/HoogBERTa.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 5 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-lst-nectec-hoogberta/safety on Hugging Bay.

Q: Will lst-nectec/HoogBERTa 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.

lst-nectec

HoogBERTa

lst-nectec/HoogBERTa

Model details

masked-language modelingLicense: mitSHA-256 recorded for 6 of 8 filessafetensors · BIN

Content controls: not assessed.

Listed for predicting masked text; for developers working with masked language models. Catalog sources: license, cardMetadata.license, 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-lst-nectec-hoogberta/model.safetensors",
    "model.safetensors",
)

Other ways

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

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

Selected downloadmodel.safetensors575 MB · 1 file Download · 575 MB (1 file)

Open-file help

Content controls: not assessed.

Check your download →

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

5 hosted of 8 listed

Hashes recorded. Date not recorded.

File	Größe	SHA-256	Quelle	Herunterladen
Weights
`model.safetensors` Default	574.6 MB	`a1c202b7…85c7b1ca` `a1c202b7319937be1a3168c4c0592d226eee60a97e294a6e74f0b05b85c7b1ca`	Hosted	Herunterladen
`pytorch_model.bin`	574.7 MB	`25726e4d…ec514202` `25726e4de3334ef7b15690e4170540443dfdbf34c62c2170d53b153fec514202`	Upstream only	File metadata
Tokenizer & config
`config.json`	696 bytes	`9e99ad92…52211e74` `9e99ad922a4d30f745fa381d8e62f1eac648734050d157fa5346641d52211e74`	Hosted	Herunterladen
`special_tokens_map.json`	120 bytes	`7acff50d…a8e119f2` `7acff50da052b903d44ea8b559d0a1dab1e8d211d6974186bff048a2a8e119f2`	Hosted	Herunterladen
`tokenizer.json`	3.37 MB	`9f6e3589…a5050940` `9f6e3589e11bbe2567f7a872cbb0f278fd947ed72586f6de7ec3d7dfa5050940`	Hosted	Herunterladen
`tokenizer_config.json`	288 bytes	`d5c00298…ee71b34e` `d5c002988b8b455a093c4b76123bda05c38bc974666cee9f9893c537ee71b34e`	Hosted	Herunterladen
Docs
`.gitattributes`	1.48 KB	—	Upstream only	File metadata
`README.md`	3.75 KB	—	Upstream only	File metadata

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.

HoogBERTa

Einen Download prüfen

Cookies