MNLP_M2_document_encoder
Can I run MNLP_M2_document_encoder on my computer?
It depends on your memory, processor, file format and runtime. Hugging Bay offers 7 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.
MNLP_M2_document_encoder 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 .
Recorded SHA-256 for model.safetensors: 4b13b8593311201737b0acaa24f33c39e2d07953e5ba13fc6ff0c6242d13e1b5. 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 · 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 at the model source. Popularity counters are source-reported, not measured by Hugging Bay. Availability checked .
Youssefbou62/MNLP_M2_document_encoderInformations sur le modèle
MNLP_M2_document_encoder is an embedding model for sentence similarity and retrieval. The primary file is model.safetensors (670 MB). The primary file needs about 2 GB free for the selected file (file plus room to run it). License: MIT. The SHA-256 prefix is 4b13b8593311. 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.
Contenu inclus
7 hosted of 24 listed
À propos de ce modèle
External Hugging Face catalog record for Youssefbou62/MNLP_M2_document_encoder. Task: sentence similarity. Library: sentence transformers. Languages: en. Includes 12 model-card evaluation signals. Popularity signal at import: 90 downloads and 0 likes.
Informations clés
- Hosted here
- 7 hosted of 24 listed
- Full repo upstream
- 5.36 GB
- Recommended file
- 670.3 MB · model.safetensors
- Languages
- en
- Format
- safetensors · ONNX · BIN
- File hashes
- Hashes recorded. Date not recorded.
Licence et source
License: mit
7 hosted of 24 listed
Check the license text and keep the required notices when you use or share the files.
Upstream source →- Task
- sentence similarity and retrieval
- Hosted here
- 7 files, 671 MB
- Full repo upstream
- 5.36 GB
- Recommended file
- 670.3 MB · model.safetensors
- Files
- 7 hosted of 24 listed
- Download
- Download here (7 hosted files)
- Added to Hugging Bay
- Updated at source
FAQ
What is this model?
Youssefbou62/MNLP_M2_document_encoder is an embedding model for sentence similarity and retrieval published by Youssefbou62, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for sentence similarity: Youssefbou62/MNLP_M2_document_encoder · sentence 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: 7 files, 671 MB. Full repo upstream: 5.36 GB. The recommended download, model.safetensors, is 670.3 MB.
What can I download here?
Hosted here: 7 files, 671 MB. Full repo upstream: 5.36 GB. The original release is at https://huggingface.co/Youssefbou62/MNLP_M2_document_encoder.
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-youssefbou62-mnlp-m2-document-encoder/safety on Hugging Bay.
Will Youssefbou62/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.