sciembed-ctx-2048 safetensors download | Hugging Bay

Q: What is this model?

anon-nlp/sciembed-ctx-2048 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-ctx-2048

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 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/anon-nlp/sciembed-ctx-2048.

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-ctx-2048/safety on Hugging Bay.

Q: Will anon-nlp/sciembed-ctx-2048 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-ctx-2048

Can I run sciembed-ctx-2048 on my computer?

It depends on your memory, processor, file format and runtime. Hugging Bay offers 10 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.

sciembed-ctx-2048 is an embedding model for text embeddings. 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 2026-10-22.

Recorded SHA-256 for model.safetensors: d8dfca5b7f39e10664ff94f9f4329a63d8da0da32c41a9922a7b1db62234ed45. 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 2026-08-04 at the model source. Popularity counters are source-reported, not measured by Hugging Bay. Availability checked 2026-10-22.

anon-nlp/sciembed-ctx-2048

Model details

text embeddingsLicense: mitSHA-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, tags, task.

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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-ctx-2048/model.safetensors",
    "model.safetensors",
)

Other ways

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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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