bert-large-NER safetensors download (1.33 GB) | Hugging Bay

dslim

bert-large-NER

Can I run bert-large-NER on my computer?

It depends on your memory, processor, file format and runtime. Hugging Bay offers 11 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.

bert-large-NER is an open-weights language model for token 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: 81d6a7a3967f136e18bac045a2c8c0ab30f39ae70268129e60255afa21d4205b. 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 2026-08-28 at the model source. Popularity counters are source-reported, not measured by Hugging Bay. Availability checked 2026-10-22.

dslim/bert-large-NER

Model details

token classificationLicense: mitSHA-256 recorded for 11 of 17 filessafetensors · ONNX · BIN · H5

Content controls: not assessed.

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

Can I run it?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-dslim-bert-large-ner/model.safetensors",
    "model.safetensors",
)

Other ways

This file cannot open in the app. The app supports one GGUF file at a time.

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11 hosted of 17 listed · Hashes recorded. Date not recorded.

Selected downloadmodel.safetensors1.33 GB · 1 file Download · 1.33 GB (1 file)

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Informations sur le modèle

bert-large-NER is an open-weights language model for token classification. The primary file is model.safetensors (1.33 GB). The primary file needs about 3 GB free for the selected file (file plus room to run it). License: MIT. The SHA-256 prefix is 81d6a7a3967f. The primary Download is available now. No tested run commands for this file yet. See Files for current download availability. The size and hash details refer to the selected file, not every file in the repository. The memory figure is estimated from recorded file size with working room included.

Contenu inclus

11 hosted of 17 listed

Weights

Tokenizer & config

README, LICENSE & .gitattributes

À propos de ce modèle

External Hugging Face catalog record for dslim/bert-large-NER. Task: token classification. Library: transformers. Languages: en. Datasets referenced by card metadata: conll2003. Includes 5 model-card evaluation signals. Popularity signal at import: 138,158 downloads and 163 likes.

Informations clés

Hosted here: 11 hosted of 17 listed
Full repo upstream: 6.67 GB
Recommended file: 1.33 GB · model.safetensors
Languages: en
Format: safetensors · ONNX · BIN · H5
File hashes: Hashes recorded. Date not recorded.

Licence et source

License: mit

11 hosted of 17 listed

Check the license text and keep the required notices when you use or share the files.

Upstream source →

See the JSON record →

License: MIT. Free to use and share, keep the credit notice
Task: token classification
Hosted here: at least 11 listed files; full count and size unknown
Full repo upstream: 6.67 GB
Recommended file: 1.33 GB · model.safetensors
Files: 11 hosted of 17 listed
Download: Download here (11 hosted files)
Added to Hugging Bay: Jun 29, 2026
Updated at source: Aug 28, 2026
Source: dslim/bert-large-NER

FAQ

What is this model?

dslim/bert-large-NER is an open-weights language model for token classification published by dslim, added to Hugging Bay Jun 29, 2026. Model from Hugging Face for token classification: dslim/bert-large-NER · transformers

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.

How big is it?

Hosted here: at least 11 listed files; full count and size unknown. Full repo upstream: 6.67 GB. The recommended download, model.safetensors, is 1.33 GB.

What can I download here?

Hosted here: at least 11 listed files; full count and size unknown. Full repo upstream: 6.67 GB. The original release is at https://huggingface.co/dslim/bert-large-NER.

File checks and computer fit

File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 11 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-dslim-bert-large-ner/safety on Hugging Bay.

Will dslim/bert-large-NER 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.