MNLP_M3_document_encoder safetensors download | Hugging Bay

MNLP_M3_document_encoder

Can I run MNLP_M3_document_encoder on my computer?

It depends on your memory, processor, file format and runtime. Hugging Bay offers 8 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_M3_document_encoder is an embedding model for text embeddings. 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 2026-10-22.

Recorded SHA-256 for model.safetensors: 0d4db737f56aaea90796b5a8d219de0eee958295a575c611f6b417ad340151da. 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 2026-10-21 · 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 2026-09-24 at the model source. Popularity counters are source-reported, not measured by Hugging Bay. Availability checked 2026-10-22.

Oussama1209/MNLP_M3_document_encoder

Model details

text embeddingsLicense: mitSHA-256 recorded for 8 of 12 filessafetensors

Content controls: not assessed.

The catalog lists this model for turning text into vectors. Catalog sources: license, cardMetadata.license, cardMetadata.libraryName, modality, task, cardMetadata.pipelineTag.

View as JSON →

Your next step

Use it from code

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-oussama1209-mnlp-m3-document-encoder/model.safetensors",
    "model.safetensors",
)

Other ways

This file cannot open in the app. The app supports one GGUF file at a time.

See app requirements

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

Selected downloadmodel.safetensors438 MB · 1 file Download · 438 MB (1 file)

Open-file help

Content controls: not assessed.

Check your download →

Compare your file’s SHA-256 with the recorded hash.

Informations sur le modèle

MNLP_M3_document_encoder is an embedding model for text embeddings. The primary file is model.safetensors (438 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 0d4db737f56a. 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

8 hosted of 12 listed

Weights

Tokenizer & config

README, LICENSE & .gitattributes

À propos de ce modèle

External Hugging Face catalog record for Oussama1209/MNLP_M3_document_encoder. Task: feature extraction. Library: sentence transformers. Languages: en. Includes 12 model-card evaluation signals. Popularity signal at import: 91 downloads and 0 likes.

Informations clés

Hosted here: 8 hosted of 12 listed
Full repo upstream: 439 MB
Recommended file: 438 MB · model.safetensors
Languages: en
Format: safetensors
File hashes: Hashes recorded. Date not recorded.

Licence et source

License: mit

8 hosted of 12 listed

Check the license text and keep the required notices when you use or share the files.

Upstream source →

See the JSON record →

Download check: Can download · bytes verified · signed · current
Checked: 2026-10-22T04:32:44.870Z
License: MIT. Free to use and share, keep the credit notice
Task: text embeddings
Hosted here: at least 8 listed files; full count and size unknown
Full repo upstream: 439 MB
Recommended file: 438 MB · model.safetensors
Files: 8 hosted of 12 listed
Download: Download here (8 hosted files)
Added to Hugging Bay: Jun 30, 2026
Updated at source: Sep 24, 2026
Source: Oussama1209/MNLP_M3_document_encoder

FAQ

What is this model?

Oussama1209/MNLP_M3_document_encoder is an embedding model for text embeddings published by Oussama1209, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for feature extraction: Oussama1209/MNLP_M3_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: at least 8 listed files; full count and size unknown. Full repo upstream: 439 MB. The recommended download, model.safetensors, is 438 MB.

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/Oussama1209/MNLP_M3_document_encoder.

File checks and computer fit

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-oussama1209-mnlp-m3-document-encoder/safety on Hugging Bay.

Will Oussama1209/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.