ModernBERT-DAPT-Embed-DAPT-Math download | Hugging Bay

Q: What is this model?

Master-thesis-NAP/ModernBERT-DAPT-Embed-DAPT-Math is an embedding model for sentence similarity and retrieval published by Master-thesis-NAP, added to Hugging Bay Jun 30, 2026. Model from Hugging Face: Master-thesis-NAP/ModernBERT-DAPT-Embed-DAPT-Math

Q: Can I use it commercially?

It is released under the apache-2.0 license. Commercial use is allowed. Permissive open license: commercial use, modification, and redistribution are permitted.

Q: How big is it?

Hosted here: at least 10 listed files; full count and size unknown. The full repository size is not recorded. The recommended download, model.safetensors, is 596.1 MB.

Q: What can I download here?

Hosted here: at least 10 listed files; full count and size unknown. Full repo upstream: unknown. The original release is at https://huggingface.co/Master-thesis-NAP/ModernBERT-DAPT-Embed-DAPT-Math.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 10 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-master-thesis-nap-modernbert-dapt-embed-dapt-math/safety on Hugging Bay.

Q: Will Master-thesis-NAP/ModernBERT-DAPT-Embed-DAPT-Math 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.

Master-thesis-NAP

ModernBERT-DAPT-Embed-DAPT-Math

Master-thesis-NAP/ModernBERT-DAPT-Embed-DAPT-Math

Model details

sentence similarity and retrievalLicense: apache-2.0SHA-256 recorded for 10 of 11 filessafetensors

Content controls: not assessed.

The catalog lists this model for checking whether two sentences mean similar things. Catalog sources: license, task.

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from urllib.request import urlretrieve

urlretrieve(
    "https://huggingbay.xyz/api/downloads/hf-model-master-thesis-nap-modernbert-dapt-embed-dapt-math/model.safetensors",
    "model.safetensors",
)

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

Selected downloadmodel.safetensors596 MB · 1 file Download · 596 MB (1 file)

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10 hosted of 11 listed

Hashes recorded. Date not recorded.

File	Size	SHA-256	Source	Download
Weights
`model.safetensors` Default	596.1 MB	`9fb0c713…9fe42fb0` `9fb0c71301a44ea0bac691b487523e3cf58654a5e6cf5daeb1c1f0cc9fe42fb0`	Hosted	Download
Tokenizer & config
`1_Pooling/config.json`	296 bytes	`1c8bc7bd…e154ec1c` `1c8bc7bd750c5c20d8707f1c5c578f5d69bb3d1d5ebcf4b2fde5128de154ec1c`	Hosted	Download
`config.json`	1.21 KB	`82779b8d…a97218d2` `82779b8d52566907948b15d853d113d24275004831b3cec0164af54ca97218d2`	Hosted	Download
`config_sentence_transformers.json`	205 bytes	`1c962cd1…2b936240` `1c962cd1cf6f96e82ce8aa900d5a2b8a572c46635eea564bef590be22b936240`	Hosted	Download
`sentence_bert_config.json`	54 bytes	`eb9b44b1…40776eb1` `eb9b44b13c0f52a3b3685c3b1cbdea1ba8b04bea123b98f61610048940776eb1`	Hosted	Download
`special_tokens_map.json`	694 bytes	`ea97ecdb…1be81049` `ea97ecdbcc73713039d8d64dbb05e3689495c96657fbd9a18f5bed381be81049`	Hosted	Download
`tokenizer.json`	3.58 MB	`bb637767…f6ac543d` `bb637767e8dfb8044597df6c58243bff2e592ae9e3b310c0bbdb8591f6ac543d`	Hosted	Download
`tokenizer_config.json`	21 KB	`7d0202a5…80d36fac` `7d0202a5a52b64763047daff52b5da0e399b1e1b90a131a3063dc56280d36fac`	Hosted	Download
`modules.json`	349 bytes	`84e40c8e…7cf642cf` `84e40c8e006c9b1d6c122e02cba9b02458120b5fb0c87b746c41e0207cf642cf`	Hosted	Download
Docs
`README.md`	46.2 KB	`685b57e8…37a30acf` `685b57e8b3ead209e6cf592cc3f4645bf733bfc6a1cf263812d4168337a30acf`	Hosted	Download
`.gitattributes`	0 bytes	—	Upstream only	File metadata

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ModernBERT-DAPT-Embed-DAPT-Math

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