MNLP_M3_document_encoder safetensors download | Hugging Bay

Q: What is this model?

RikoteMaster/MNLP_M3_document_encoder is an embedding model for text embeddings published by RikoteMaster, added to Hugging Bay Sep 29, 2026. Model from Hugging Face for feature extraction: RikoteMaster/MNLP_M3_document_encoder · sentence transformers

Q: Can I use it commercially?

It is released under the apache-2.0 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: 445.1 MB. The recommended download, model.safetensors, is 428 MB.

Q: What can I download here?

Hosted here: at least 8 listed files; full count and size unknown. Full repo upstream: 445.1 MB. The original release is at https://huggingface.co/RikoteMaster/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-rikotemaster-mnlp-m3-document-encoder/safety on Hugging Bay.

Q: Will RikoteMaster/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.

RikoteMaster

MNLP_M3_document_encoder

RikoteMaster/MNLP_M3_document_encoder

Model details

text embeddingsLicense: apache-2.0SHA-256 recorded for 8 of 11 filessafetensors

Content controls: not assessed.

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

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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-rikotemaster-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 11 listed · Hashes recorded. Date not recorded.

Selected downloadmodel.safetensors428 MB · 1 file Download · 428 MB (1 file)

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Content controls: not assessed.

Check your download →

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

8 hosted of 11 listed

Hashes recorded. Date not recorded.

File	Tamanho	SHA-256	Origem	Baixar
Weights
`model.safetensors` Default	428 MB	`4a0b56e4…7bb627bf` `4a0b56e4d96a43ad2b870f1d3e82481215f559423ec3d53da43bdd867bb627bf`	Hosted	Baixar
Tokenizer & config
`1_Pooling/config.json`	296 bytes	—	Upstream only	File metadata
`config.json`	638 bytes	`2709699b…b179a088` `2709699b7629c2dee3e2ffd838bb1a472b595fe2c1bb32460ba05d10b179a088`	Hosted	Baixar
`config_sentence_transformers.json`	205 bytes	`35b9b640…afe0405e` `35b9b6400a339efa0b962d432c75bad7335a0618aed7717da0f0c82cafe0405e`	Hosted	Baixar
`sentence_bert_config.json`	53 bytes	`ec8e29d6…5a8d0d51` `ec8e29d6dcb61b611b7d3fdd2982c4524e6ad985959fa7194eacfb655a8d0d51`	Hosted	Baixar
`special_tokens_map.json`	963 bytes	`66e573bf…a6368443` `66e573bfc6c3b062381e41274f7fd4143daaf01926888ffbd880c87aa6368443`	Hosted	Baixar
`tokenizer.json`	17.1 MB	`14917dd7…f21593cf` `14917dd757b81bc44d4af6b028367351702656670c1954e055dabdfcf21593cf`	Hosted	Baixar
`tokenizer_config.json`	1.2 KB	`a572845c…fb06881b` `a572845c401dc50c54729a11ae765fddebeb03d6fd1923e89f4ac93ffb06881b`	Hosted	Baixar
`modules.json`	349 bytes	`84e40c8e…7cf642cf` `84e40c8e006c9b1d6c122e02cba9b02458120b5fb0c87b746c41e0207cf642cf`	Hosted	Baixar
Docs
`.gitattributes`	1.57 KB	—	Upstream only	File metadata
`README.md`	1.82 KB	—	Upstream only	File metadata

Verificar um download

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

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