multiling-e5-large-instruct-claim-matching download

Q: What is this model?

Sami92/multiling-e5-large-instruct-claim-matching is an embedding model for sentence similarity and retrieval published by Sami92, added to Hugging Bay Sep 24, 2026. Model from Hugging Face for sentence similarity: Sami92/multiling-e5-large-instruct-claim-matching · sentence transformers

Q: Can I use it commercially?

It is released under the cc-by-4.0 license. Commercial use is allowed. cc-by-4.0: commercial use, modification, and redistribution are permitted with attribution.

Q: How big is it?

Hosted here: at least 8 listed files; full count and size unknown. Full repo upstream: 2.27 GB. The recommended download, model.safetensors, is 2.24 GB.

Q: What can I download here?

Hosted here: at least 8 listed files; full count and size unknown. Full repo upstream: 2.27 GB. The original release is at https://huggingface.co/Sami92/multiling-e5-large-instruct-claim-matching.

Q: 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-sami92-multiling-e5-large-instruct-claim-matching/safety on Hugging Bay.

Q: Will Sami92/multiling-e5-large-instruct-claim-matching 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.

Sami92

multiling-e5-large-instruct-claim-matching

Sami92/multiling-e5-large-instruct-claim-matching

Model details

sentence similarity and retrievalLicense: cc-by-4.0Hashes recordedsafetensors

Content controls: not assessed.

Model from Hugging Face for sentence similarity: Sami92/multiling-e5-large-instruct-claim-matching · sentence transformers

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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-sami92-multiling-e5-large-instruct-claim-matching/model.safetensors",
    "model.safetensors",
)

Other ways

8 hosted of 17 listed · Hashes recorded. Date not recorded.

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

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