MNLP_M3_document_encoder safetensors download | Hugging Bay

Q: What is this model?

OmarIDK/MNLP_M3_document_encoder is an embedding model for sentence similarity and retrieval published by OmarIDK, added to Hugging Bay Jun 30, 2026. Model from Hugging Face: OmarIDK/MNLP_M3_document_encoder

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: 11 files, 134.5 MB. The full repository size is not recorded. The recommended download, model.safetensors, is 133.5 MB.

Q: What can I download here?

Hosted here: 11 files, 134.5 MB. Full repo upstream: unknown. The original release is at https://huggingface.co/OmarIDK/MNLP_M3_document_encoder.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 11 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-omaridk-mnlp-m3-document-encoder/safety on Hugging Bay.

Q: Will OmarIDK/MNLP_M3_document_encoder 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.

OmarIDK

MNLP_M3_document_encoder

OmarIDK/MNLP_M3_document_encoder

Model details

sentence similarity and retrievalLicense: mitSHA-256 recorded for 11 of 12 filessafetensors

Content controls: not assessed.

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

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from urllib.request import urlretrieve

urlretrieve(
    "https://huggingbay.xyz/api/downloads/hf-model-omaridk-mnlp-m3-document-encoder/model.safetensors",
    "model.safetensors",
)

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

Selected downloadmodel.safetensors133 MB · 1 file Download · 133 MB (1 file)

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