sbert_nli_test safetensors download (541 MB) | Hugging Bay

sbert_nli_test

Can I run sbert_nli_test on my computer?

It depends on your memory, processor, file format and runtime. Hugging Bay offers 8 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.

sbert_nli_test is an embedding model for sentence similarity and retrieval. Model weights are learned parameters; a runtime loads them. A hosted file is an individual file Hugging Bay can serve. SHA-256 identifies exact file bytes. The availability date above applies to this file record, not the upstream metadata update date.

As of the recorded file availability check on 2026-10-22.

Recorded SHA-256 for model.safetensors: 81751782980292a5f5607d67fe01ccc891f30b323a35bc519a668bd4a7a68430. Exact file evidence · Machine-readable source facts · Run evidence and any recorded receipts. A checksum fingerprints only the named file bytes; it does not prove safety, quality, a complete multi-file selection or a successful run.

Updated 2026-10-21 · Page-copy source revision 8871bab84e1cf80aea1686a944ec335078a6c036 · Source files: apps/web/lib/model-page-template.mjs, apps/web/lib/model-page-v3.mjs, apps/web/lib/aeo-page.mjs · Full revision record

Model metadata: As of 2026-09-24 at the model source. Popularity counters are source-reported, not measured by Hugging Bay. Availability checked 2026-10-22.

akhooli/sbert_nli_test

Model details

sentence similarity and retrievalLicense: apache-2.0SHA-256 recorded for 8 of 12 filessafetensors

Content controls: not assessed.

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

Can I run it?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-akhooli-sbert-nli-test/model.safetensors",
    "model.safetensors",
)

Other ways

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8 hosted of 12 listed · Hashes recorded. Date not recorded.

Selected downloadmodel.safetensors541 MB · 1 file Download · 541 MB (1 file)

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Model facts

sbert_nli_test is an embedding model for sentence similarity and retrieval. The primary file is model.safetensors (541 MB). The primary file needs about 2 GB free for the selected file (file plus room to run it). License: Apache 2.0. The SHA-256 prefix is 817517829802. The primary Download is available now. No tested run commands for this file yet. See Files for current download availability. The size and hash details refer to the selected file, not every file in the repository. The memory figure is estimated from recorded file size with working room included.

What's included

8 hosted of 12 listed

Weights

Tokenizer & config

README, LICENSE & .gitattributes

About this model

External Hugging Face catalog record for akhooli/sbert_nli_test. Task: sentence similarity. Library: sentence transformers. Languages: ar. Base model: aubmindlab/bert-base-arabertv02. Includes 5 model-card evaluation signals. Popularity signal at import: 90 downloads and 0 likes.

Quick facts

Hosted here: 8 hosted of 12 listed
Full repo upstream: 543.4 MB
Recommended file: 540.8 MB · model.safetensors
Languages: ar
Format: safetensors
File hashes: Hashes recorded. Date not recorded.

License & source

License: apache-2.0

8 hosted of 12 listed

Check the license text and keep the required notices when you use or share the files.

Upstream source →

See the JSON record →

License: Apache 2.0. Free to use and share, keep the credit notice
Task: sentence similarity and retrieval
Hosted here: at least 8 listed files; full count and size unknown
Full repo upstream: 543.4 MB
Recommended file: 540.8 MB · model.safetensors
Files: 8 hosted of 12 listed
Download: Download here (8 hosted files)
Added to Hugging Bay: Sep 24, 2026
Updated at source: Sep 24, 2026
Source: akhooli/sbert_nli_test

FAQ

What is this model?

akhooli/sbert_nli_test is an embedding model for sentence similarity and retrieval published by akhooli, added to Hugging Bay Sep 24, 2026. Model from Hugging Face for sentence similarity: akhooli/sbert_nli_test · sentence transformers

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.

How big is it?

Hosted here: at least 8 listed files; full count and size unknown. Full repo upstream: 543.4 MB. The recommended download, model.safetensors, is 540.8 MB.

What can I download here?

Hosted here: at least 8 listed files; full count and size unknown. Full repo upstream: 543.4 MB. The original release is at https://huggingface.co/akhooli/sbert_nli_test.

File checks and computer fit

File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 8 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-akhooli-sbert-nli-test/safety on Hugging Bay.

Will akhooli/sbert_nli_test 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.