zero-shot-classification safetensors download | Hugging Bay

nahiar

zero-shot-classification

nahiar/zero-shot-classification

Model details

zero-shot classificationLicense: mitHashes recordedsafetensors · BIN · H5

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Listed for classifying text with supplied labels; for developers building text classification tools. Catalog sources: license, cardMetadata.license, task, cardMetadata.pipelineTag.

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from urllib.request import urlretrieve

urlretrieve(
    "https://huggingbay.xyz/api/downloads/hf-model-nahiar-zero-shot-classification/model.safetensors",
    "model.safetensors",
)

Other ways

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

Selected downloadmodel.safetensors2.24 GB · 1 file Download · 2.24 GB (1 file)

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Informações do modelo

zero-shot-classification is an open-weights language model for zero-shot classification. The primary file is model.safetensors (2.24 GB). The primary file needs about 4 GB free for the selected file. License: MIT. The SHA-256 prefix is 8869b0c99ad3. 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. The size line uses recorded file bytes when they are present in this model record.

O que está incluído

7 hosted of 10 listed

Weights

Tokenizer & config

README, LICENSE & .gitattributes

Sobre este modelo

External Hugging Face catalog record for nahiar/zero-shot-classification. Task: zero shot classification. Library: transformers. Languages: multilingual, en, fr, es, de, el, bg, ru. Datasets referenced by card metadata: multi_nli, xnli. Includes 2 model-card evaluation signals. Popularity signal at import: 25 downloads and 2 likes.

Informações básicas

Hosted here: 7 hosted of 10 listed
Full repo upstream: 6.74 GB
Recommended file: 2.24 GB · model.safetensors
Languages: multilingual, en, fr, es, de, el, bg, ru, tr, ar, vi, th
Format: safetensors · BIN · H5
Downloads on Hugging Face: 44
File hashes: Hashes recorded. Date not recorded.

Licença e origem

License: mit

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Upstream source →

See the JSON record →

License: MIT. Free to use and share, keep the credit notice
Task: zero-shot classification
Hosted here: at least 7 listed files; full count and size unknown
Full repo upstream: 6.74 GB
Recommended file: 2.24 GB · model.safetensors
Files: 7 hosted of 10 listed
Download: Download here (7 hosted files)
Added to Hugging Bay: Jun 30, 2026
Updated at source: Sep 3, 2026
Source: nahiar/zero-shot-classification

FAQ

What is this model?

nahiar/zero-shot-classification is an open-weights language model for zero-shot classification published by nahiar, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for zero shot classification: nahiar/zero-shot-classification · transformers

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.

How big is it?

Hosted here: at least 7 listed files; full count and size unknown. Full repo upstream: 6.74 GB. The recommended download, model.safetensors, is 2.24 GB.

What can I download here?

Hosted here: at least 7 listed files; full count and size unknown. Full repo upstream: 6.74 GB. The original release is at https://huggingface.co/nahiar/zero-shot-classification.

File checks and computer fit

File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 7 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-nahiar-zero-shot-classification/safety on Hugging Bay.

Will nahiar/zero-shot-classification 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.