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

NLPclass/Named-entity-recognition

Model details

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

Content controls: not assessed.

Listed for labeling parts of text; for developers building token classifiers. Catalog sources: license, cardMetadata.license, 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-nlpclass-named-entity-recognition/model.safetensors",
    "model.safetensors",
)

Other ways

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

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

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

Open-file help

Content controls: not assessed.

Check your download →

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

5 hosted of 7 listed

Hashes recorded. Date not recorded.

File	Tamanho	SHA-256	Origem	Baixar
Weights
`model.safetensors` Default	489.3 MB	`acd4db56…4eecfacb` `acd4db56b9a69adde41f8a92cf00387aa586d785347e60be7e446e794eecfacb`	Hosted	Baixar
Tokenizer & config
`config.json`	1.2 KB	`4b73b745…803d7774` `4b73b745dcf70983f5cf5c0095ea197cddff6db3823eddbeb21647cf803d7774`	Hosted	Baixar
`special_tokens_map.json`	828 bytes	`37b0bf6d…911ec124` `37b0bf6d341fa18d841a2f77efe4af909a5e9b79fe63f9e81f5ac61c911ec124`	Hosted	Baixar
`tokenizer.json`	2.59 MB	`3fcc98a6…3a095774` `3fcc98a61f28a8f7089894825572f2bbf22147900241f57a326159e03a095774`	Hosted	Baixar
`tokenizer_config.json`	1.38 KB	`eea48851…26bc68e7` `eea4885116d1b3e441466915d8213f818180d0a8e1c3961ed852a1fd26bc68e7`	Hosted	Baixar
Docs
`.gitattributes`	1.52 KB	—	Upstream only	File metadata
`README.md`	2.89 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.

Named-entity-recognition

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