Named-entity-recognition safetensors download | Hugging Bay

Q: What is this model?

NLPclass/Named-entity-recognition is an open-weights language model for token classification published by NLPclass, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for token classification: NLPclass/Named-entity-recognition · 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, 491.9 MB. Full repo upstream: 491.9 MB. The recommended download, model.safetensors, is 489.3 MB.

Q: What can I download here?

Hosted here: 5 files, 491.9 MB. Full repo upstream: 491.9 MB. The original release is at https://huggingface.co/NLPclass/Named-entity-recognition.

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-nlpclass-named-entity-recognition/safety on Hugging Bay.

Q: Will NLPclass/Named-entity-recognition 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.

NLPclass

Named-entity-recognition

Can I run Named-entity-recognition 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.

Named-entity-recognition is an open-weights language model for token classification. Model weights are learned parameters; a runtime loads them. Hosting files does not prove that a complete model runs.

As of the availability check on 2026-10-22.

Recorded SHA-256 for model.safetensors: acd4db56b9a69adde41f8a92cf00387aa586d785347e60be7e446e794eecfacb. File evidence · Machine-readable facts · Run evidence and any recorded receipts · Proof Lab measurement policy. A checksum verifies byte identity, not safety; this answer asserts no measured runtime result.

Updated 2026-10-21 · Page text: As of 2026-10-21 · Content revision

Model metadata: As of 2026-09-23 at the model source. Popularity counters are source-reported, not measured by Hugging Bay. Availability checked 2026-10-22.

NLPclass/Named-entity-recognition

Model details

token classificationLicense: mitSHA-256 recorded for 5 of 7 filessafetensors

Content controls: not assessed.

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

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from urllib.request import urlretrieve

urlretrieve(
    "https://huggingbay.xyz/api/downloads/hf-model-nlpclass-named-entity-recognition/model.safetensors",
    "model.safetensors",
)

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

Selected downloadmodel.safetensors489 MB · 1 file Download · 489 MB (1 file)

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