MNLP_M3_document_encoder safetensors download | Hugging Bay

Q: What is this model?

nililba/MNLP_M3_document_encoder is an embedding model for text embeddings published by nililba, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for feature extraction: nililba/MNLP_M3_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: 134.5 MB. The recommended download, model.safetensors, is 133.5 MB.

Q: What can I download here?

Hosted here: at least 8 listed files; full count and size unknown. Full repo upstream: 134.5 MB. The original release is at https://huggingface.co/nililba/MNLP_M3_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-nililba-mnlp-m3-document-encoder/safety on Hugging Bay.

Q: Will nililba/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.

nililba

MNLP_M3_document_encoder

nililba/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-nililba-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.safetensors133 MB · 1 file Download · 133 MB (1 file)

Open-file help

Content controls: not assessed.

Check your download →

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

8 hosted of 12 listed

Hashes recorded. Date not recorded.

File	Tamaño	SHA-256	Origen	Descargar
Weights
`model.safetensors` Default	133.5 MB	`ea1d11a3…805ee3e8` `ea1d11a3f23d14fe09fc1826fc7944e89c09a634d2217d57a21dd136805ee3e8`	Hosted	Descargar
Tokenizer & config
`1_Pooling/config.json`	296 bytes	—	Upstream only	File metadata
`config.json`	661 bytes	`ea5db38d…ca752d83` `ea5db38dbfeb8be8a4b3a2923f0ab890d6128f340013608ca1990486ca752d83`	Hosted	Descargar
`config_sentence_transformers.json`	195 bytes	`f6aed622…eb98a711` `f6aed62213fddf09166532e2fdc0590c940534c5d33e9a5fc89b9755eb98a711`	Hosted	Descargar
`sentence_bert_config.json`	52 bytes	`84e39fda…2a693cbf` `84e39fda68ccbff05bfa723ae9c0e70e23e2ec373b76e0f8c6e71af72a693cbf`	Hosted	Descargar
`special_tokens_map.json`	695 bytes	`5d5b662e…a350503a` `5d5b662e421ea9fac075174bb0688ee0d9431699900b90662acd44b2a350503a`	Hosted	Descargar
`tokenizer.json`	711.4 KB	`d241a60d…1f9e5c66` `d241a60d5e8f04cc1b2b3e9ef7a4921b27bf526d9f6050ab90f9267a1f9e5c66`	Hosted	Descargar
`tokenizer_config.json`	1.27 KB	`7b082b48…171186a0` `7b082b48a08a0b5c5939d99472e33addce3d96202155e33f7928cecd171186a0`	Hosted	Descargar
`vocab.txt`	231.5 KB	—	Upstream only	File metadata
`modules.json`	349 bytes	`84e40c8e…7cf642cf` `84e40c8e006c9b1d6c122e02cba9b02458120b5fb0c87b746c41e0207cf642cf`	Hosted	Descargar
Docs
`.gitattributes`	1.52 KB	—	Upstream only	File metadata
`README.md`	94.8 KB	—	Upstream only	File metadata

Comprobar una descarga

In the folder where you saved model.safetensors, run:

macOS

shasum -a 256 -- 'model.safetensors'

Linux

sha256sum -- 'model.safetensors'

Windows

Get-FileHash -LiteralPath 'model.safetensors' -Algorithm SHA256

Compare the result with the recorded SHA-256.

MNLP_M3_document_encoder

Comprobar una descarga

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