moralBERT-predict-subversion-in-text download | Hugging Bay

Q: What is this model?

vjosap/moralBERT-predict-subversion-in-text is an open-weights language model for text classification published by vjosap, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for text classification: vjosap/moralBERT-predict-subversion-in-text · unknown

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: 443.6 MB. The recommended download, model.safetensors, is 442.7 MB.

Q: What can I download here?

Hosted here: at least 7 listed files; full count and size unknown. Full repo upstream: 443.6 MB. The original release is at https://huggingface.co/vjosap/moralBERT-predict-subversion-in-text.

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-vjosap-moralbert-predict-subversion-in-text/safety on Hugging Bay.

Q: Will vjosap/moralBERT-predict-subversion-in-text 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.

vjosap

moralBERT-predict-subversion-in-text

vjosap/moralBERT-predict-subversion-in-text

Model details

text classificationLicense: mitSHA-256 recorded for 7 of 8 filessafetensors

Content controls: not assessed.

The catalog lists this model for sorting text into categories. Catalog sources: license, cardMetadata.license, task, cardMetadata.pipelineTag.

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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-vjosap-moralbert-predict-subversion-in-text/model.safetensors",
    "model.safetensors",
)

Other ways

This file cannot open in the app. The app supports one GGUF file at a time.

See app requirements

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

Selected downloadmodel.safetensors443 MB · 1 file Download · 443 MB (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	Tamanho	SHA-256	Origem	Baixar
Weights
`model.safetensors` Default	442.7 MB	`5a23ace1…34e5b68d` `5a23ace1d0d807c6ee244e91de79cf745ba7915ed4587a25b962093134e5b68d`	Hosted	Baixar
Tokenizer & config
`config.json`	22 bytes	`87de6c1c…8a9b76f0` `87de6c1ca54f65728a6489bc64fef05f38bf5eea2f8adc4cc8d82cea8a9b76f0`	Hosted	Baixar
`tokenizer_config.json`	1.19 KB	`f62a57a7…6285968e` `f62a57a75856b93282501c92a86f62b169997c81e93cf6f75b7cc15d6285968e`	Hosted	Baixar
`vocab.txt`	231.5 KB	`07eced37…992038a3` `07eced375cec144d27c900241f3e339478dec958f92fddbc551f295c992038a3`	Hosted	Baixar
`special_tokens_map.json`	125 bytes	`b6d346be…76237ee3` `b6d346be366a7d1d48332dbc9fdf3bf8960b5d879522b7799ddba59e76237ee3`	Hosted	Baixar
`tokenizer.json`	711.4 KB	`d241a60d…1f9e5c66` `d241a60d5e8f04cc1b2b3e9ef7a4921b27bf526d9f6050ab90f9267a1f9e5c66`	Hosted	Baixar
Docs
`.gitattributes`	1.52 KB	—	Upstream only	File metadata
`README.md`	355 bytes	`97a22f41…50c00732` `97a22f413cba281c4c71ba2c0f86e339f9876f65bc7e53c257ff71f050c00732`	Hosted	Baixar

Verificar um download

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.

moralBERT-predict-subversion-in-text

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