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

text embeddingsLicense: mitHashes recordedsafetensors

Content controls: not assessed.

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

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anon-nlp/sciembed-base
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License: mit
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sciembed-base

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