RoBERTo-v2 safetensors download (556 MB) | Hugging Bay

Q: What is this model?

absltnull/RoBERTo-v2 is an open-weights language model for text classification published by absltnull, added to Hugging Bay Sep 23, 2026. Model from Hugging Face for text classification: absltnull/RoBERTo-v2 · 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: 4 files, 573.2 MB. Full repo upstream: 573.3 MB. The recommended download, model.safetensors, is 556.1 MB.

Q: What can I download here?

Hosted here: 4 files, 573.2 MB. Full repo upstream: 573.3 MB. The original release is at https://huggingface.co/absltnull/RoBERTo-v2.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 4 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-absltnull-roberto-v2/safety on Hugging Bay.

Q: Will absltnull/RoBERTo-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.

absltnull

RoBERTo-v2

absltnull/RoBERTo-v2

Model details

text classificationLicense: mitSHA-256 recorded for 5 of 9 filessafetensors · BIN

Content controls: not assessed.

Listed for labeling text; for developers building text classifiers. Catalog sources: license, cardMetadata.license, baseModel, 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-absltnull-roberto-v2/model.safetensors",
    "model.safetensors",
)

Other ways

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

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

Selected downloadmodel.safetensors556 MB · 1 file Download · 556 MB (1 file)

Open-file help

Content controls: not assessed.

Check your download →

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

4 hosted of 9 listed

Hashes recorded. Date not recorded.

File	Tamanho	SHA-256	Origem	Baixar
Weights
`model.safetensors` Default	556.1 MB	`845b2375…c56d87cd` `845b2375dca890e25b9b3dce6cd68e93a11aaf2b0101df319c32f139c56d87cd`	Hosted	Baixar
`training_args.bin`	5.2 KB	`4a122d27…c4c1540e` `4a122d27f1f59b9126e9fc35e39012fcfdb8290578d107d6c0335ce9c4c1540e`	Upstream only	File metadata
Tokenizer & config
`config.json`	937 bytes	`bb9b579c…1a04ea96` `bb9b579ce7d80db110559800dcb496fe243ceb521d143ee52aab90d71a04ea96`	Hosted	Baixar
`confusion_matrix.png`	53.4 KB	—	Upstream only	File metadata
`model_comparison.png`	50.5 KB	—	Upstream only	File metadata
`tokenizer.json`	17.1 MB	`acbd420e…85307153` `acbd420e2269cdc1ef45332d3d5c418be4aef6b8cb5a0b7ccae0893485307153`	Hosted	Baixar
`tokenizer_config.json`	343 bytes	`5d84c938…1a4337f6` `5d84c938d902dbd684af806ccc920e4c99812d897b0f271eebf856361a4337f6`	Hosted	Baixar
Docs
`.gitattributes`	1.57 KB	—	Upstream only	File metadata
`README.md`	7.54 KB	—	Upstream only	File metadata

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.

RoBERTo-v2

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