modernbert_large_slop_classifier_v3 download | Hugging Bay

Q: What is this model?

underscore2/modernbert_large_slop_classifier_v3 is an open-weights language model for text classification published by underscore2, added to Hugging Bay Sep 24, 2026. Model from Hugging Face for text classification: underscore2/modernbert_large_slop_classifier_v3 · 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 5 listed files; full count and size unknown. Full repo upstream: 1.59 GB. The recommended download, model.safetensors, is 1.58 GB.

Q: What can I download here?

Hosted here: at least 5 listed files; full count and size unknown. Full repo upstream: 1.59 GB. The original release is at https://huggingface.co/underscore2/modernbert_large_slop_classifier_v3.

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-underscore2-modernbert-large-slop-classifier-v3/safety on Hugging Bay.

Q: Will underscore2/modernbert_large_slop_classifier_v3 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.

underscore2

modernbert_large_slop_classifier_v3

Can I run modernbert_large_slop_classifier_v3 on my computer?

It depends on your memory, processor, file format and runtime. Hugging Bay offers 5 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.

modernbert_large_slop_classifier_v3 is an open-weights language model for text classification. 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: 956e68ef4bba322fbdaf88675ddce29d2b9dcf8298b55dc8e15cc823d7ec77bf. 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 2026-09-24 at the model source. Popularity counters are source-reported, not measured by Hugging Bay. Availability checked 2026-10-22.

underscore2/modernbert_large_slop_classifier_v3

Model details

text classificationLicense: apache-2.0SHA-256 recorded for 7 of 9 filessafetensors · BIN

Content controls: not assessed.

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

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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-underscore2-modernbert-large-slop-classifier-v3/model.safetensors",
    "model.safetensors",
)

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

Selected downloadmodel.safetensors1.58 GB · 1 file Download · 1.58 GB (1 file)

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