MNLP_M2_document_encoder safetensors download | Hugging Bay

Q: What is this model?

raphassaraf/MNLP_M2_document_encoder is an embedding model for text embeddings published by raphassaraf, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for feature extraction: raphassaraf/MNLP_M2_document_encoder · sentence transformers

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 8 listed files; full count and size unknown. Full repo upstream: 439 MB. The recommended download, model.safetensors, is 438 MB.

Q: What can I download here?

Hosted here: at least 8 listed files; full count and size unknown. Full repo upstream: 439 MB. The original release is at https://huggingface.co/raphassaraf/MNLP_M2_document_encoder.

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-raphassaraf-mnlp-m2-document-encoder/safety on Hugging Bay.

Q: Will raphassaraf/MNLP_M2_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.

raphassaraf

MNLP_M2_document_encoder

raphassaraf/MNLP_M2_document_encoder

text embeddingsLicense: mitHashes recordedsafetensors

Content controls: not assessed.

Model from Hugging Face for feature extraction: raphassaraf/MNLP_M2_document_encoder · sentence transformers

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MNLP_M2_document_encoder

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