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

Q: 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

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

Q: 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.

Q: 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.

Q: 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.

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. Hosting files does not prove that a complete model runs.

As of the availability check on 2026-10-21.

Recorded SHA-256 for model.safetensors: 81d6a7a3967f136e18bac045a2c8c0ab30f39ae70268129e60255afa21d4205b. 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 2026-08-28 at the model source. Popularity counters are source-reported, not measured by Hugging Bay. Availability checked 2026-10-21.

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.

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.

See app requirements

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

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

Open-file help

Content controls: not assessed.

Check your download →

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

11 hosted of 17 listed

Hashes recorded. Date not recorded.

File	Taille	SHA-256	Source	Télécharger
Weights
`model.safetensors` Default	1.33 GB	`81d6a7a3…21d4205b` `81d6a7a3967f136e18bac045a2c8c0ab30f39ae70268129e60255afa21d4205b`	Hosted	Télécharger
`onnx/model.onnx`	1.33 GB	`46ba1e05…4c44106b` `46ba1e057362a10e8163f69a2c9ef1cbb609e9eca6ab265835d8f7fa4c44106b`	Hosted	Télécharger
`pytorch_model.bin`	1.33 GB	`db4d615a…ff7cea3d` `db4d615a10a12cfe134388d43d8fba48e909e7f7afa3e4d3b1bd2c24ff7cea3d`	Hosted	Télécharger
Tokenizer & config
`config.json`	1.45 KB	`e11b71c7…ff304ced` `e11b71c7e638df545a75e3ff926d3eb77024636dee997d9be986dce3ff304ced`	Hosted	Télécharger
`flax_model.msgpack`	1.33 GB	`d63d3952…6a50f171` `d63d39520929bbeab16344157582be46f09a3ab43095b14f1b1586636a50f171`	Hosted	Télécharger
`onnx/added_tokens.json`	82 bytes	—	Upstream only	File metadata
`onnx/config.json`	1.2 KB	`ee4dd194…2924f1fa` `ee4dd194a147de250824b128af5be48d92f5a36c1fc3404aa670f6f62924f1fa`	Hosted	Télécharger
`onnx/special_tokens_map.json`	125 bytes	—	Upstream only	File metadata
`onnx/tokenizer.json`	668.9 KB	—	Upstream only	File metadata
`onnx/tokenizer_config.json`	1.3 KB	—	Upstream only	File metadata
`onnx/vocab.txt`	213.4 KB	—	Upstream only	File metadata
`tf_model.h5`	1.33 GB	`febce5a7…bab172ba` `febce5a7915f2c894cdeb81cbe53bcc06ff3a8c22a96eaf9605aea0bbab172ba`	Hosted	Télécharger
`tokenizer_config.json`	40 bytes	`ec70da9a…5a5580b3` `ec70da9a619641c3b56e62cb949b8a07f2fdafdb8389b2c72649fb235a5580b3`	Hosted	Télécharger
`vocab.txt`	213.4 KB	`eeaa9875…1df93d02` `eeaa9875b23b04b4c54ef759d03db9d1ba1554838f8fb26c5d96fa551df93d02`	Hosted	Télécharger
`special_tokens_map.json`	112 bytes	`303df45a…5ec200e3` `303df45a03609e4ead04bc3dc1536d0ab19b5358db685b6f3da123d05ec200e3`	Hosted	Télécharger
Docs
`.gitattributes`	445 bytes	—	Upstream only	File metadata
`README.md`	5.92 KB	`88417a34…f3f68205` `88417a340bab3ff5b06e7c6fcdb89600068a2f4612918b20e909cd62f3f68205`	Hosted	Télécharger

Vérifier un téléchargement

In the folder where you saved model.safetensors, run:

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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.

bert-large-NER

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

Vérifier un téléchargement

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