NERGAL safetensors download (2.24 GB) | Hugging Bay

Q: What is this model?

SlayerLab/NERGAL is an open-weights language model for token classification published by SlayerLab, added to Hugging Bay Sep 24, 2026. Model from Hugging Face for token classification: SlayerLab/NERGAL · 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: at least 5 listed files; full count and size unknown. Full repo upstream: 2.26 GB. The recommended download, model.safetensors, is 2.24 GB.

Q: What can I download here?

Hosted here: at least 5 listed files; full count and size unknown. Full repo upstream: 2.26 GB. The original release is at https://huggingface.co/SlayerLab/NERGAL.

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-slayerlab-nergal/safety on Hugging Bay.

Q: Will SlayerLab/NERGAL 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.

SlayerLab

NERGAL

SlayerLab/NERGAL

Model details

token classificationLicense: mitSHA-256 recorded for 8 of 15 filessafetensors

Content controls: not assessed.

The catalog lists this model for labeling parts of text. Catalog sources: license, cardMetadata.license, baseModel, task, cardMetadata.pipelineTag.

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from urllib.request import urlretrieve

urlretrieve(
    "https://huggingbay.xyz/api/downloads/hf-model-slayerlab-nergal/model.safetensors",
    "model.safetensors",
)

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5 hosted of 15 listed · Hashes recorded. Date not recorded.

Selected downloadmodel.safetensors2.24 GB · 1 file Download · 2.24 GB (1 file)

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