sciembed-base safetensors download (596 MB) | Hugging Bay

Q: What is this model?

anon-nlp/sciembed-base is an embedding model for text embeddings published by anon-nlp, added to Hugging Bay Jun 30, 2026. Model from Hugging Face: anon-nlp/sciembed-base

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: 10 files, 599.7 MB. The full repository size is not recorded. The recommended download, model.safetensors, is 596.1 MB.

Q: What can I download here?

Hosted here: 10 files, 599.7 MB. Full repo upstream: unknown. The original release is at https://huggingface.co/anon-nlp/sciembed-base.

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-anon-nlp-sciembed-base/safety on Hugging Bay.

Q: Will anon-nlp/sciembed-base 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.

anon-nlp

sciembed-base

anon-nlp/sciembed-base

Model details

text embeddingsLicense: mitHashes recordedsafetensors

Content controls: not assessed.

Model from Hugging Face: anon-nlp/sciembed-base

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-anon-nlp-sciembed-base/model.safetensors",
    "model.safetensors",
)

Other ways

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	Taille	SHA-256	Source	Télécharger
Weights
`model.safetensors` Default	596.1 MB	`6e146c6f…8b9a16a7` `6e146c6f40261eadde5805dae5d8ce68723d2becd1502d9c9765353b8b9a16a7`	Hosted	Télécharger
Tokenizer & config
`1_Pooling/config.json`	312 bytes	`35bbd47d…cc8ebcc6` `35bbd47d7fdf1e378db6130bcc668b09d1aa67a7bbf7c8f89a9c71f4cc8ebcc6`	Hosted	Télécharger
`config.json`	1.21 KB	`f295786e…0f70a9dd` `f295786e36cabd2023fd17bbf048f355926bb80a9ced63d22826f3310f70a9dd`	Hosted	Télécharger
`config_sentence_transformers.json`	283 bytes	`342c797d…377fab03` `342c797d5a0300aa094bf8944d006c9f23a6851475cb26c4c2d7e06e377fab03`	Hosted	Télécharger
`modules.json`	229 bytes	`8f4b264b…b3145460` `8f4b264b80206c830bebbdcae377e137925650a433b689343a63bdc9b3145460`	Hosted	Télécharger
`sentence_bert_config.json`	57 bytes	`948201d8…ee986529` `948201d8329907aae938fa62f9ceeed53f5694dacc2b87b9f3b78b37ee986529`	Hosted	Télécharger
`special_tokens_map.json`	694 bytes	`ea97ecdb…1be81049` `ea97ecdbcc73713039d8d64dbb05e3689495c96657fbd9a18f5bed381be81049`	Hosted	Télécharger
`tokenizer.json`	3.58 MB	`3703d011…28f8f09e` `3703d011b3ee259e00b59b60772f8fd54998d79e8fa5a1388d507eff28f8f09e`	Hosted	Télécharger
`tokenizer_config.json`	20.8 KB	`c5a7dfd4…e0ff1c17` `c5a7dfd44d93c5d7ed9b2ddcd7a6018e935ec7d53f1de45910ea9868e0ff1c17`	Hosted	Télécharger
Docs
`README.md`	1.32 KB	`443e7578…bd3e4765` `443e7578c0f97dc172301074a26074c633187e9676604085a6848b51bd3e4765`	Hosted	Télécharger
`.gitattributes`	0 bytes	—	Upstream only	File metadata

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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.

sciembed-base

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