darmm-embedding-multilingual download | Hugging Bay

Q: What is this model?

Darmm/darmm-embedding-multilingual is an embedding model for sentence similarity and retrieval published by Darmm, added to Hugging Bay Sep 25, 2026. Model from Hugging Face for sentence similarity: Darmm/darmm-embedding-multilingual · unknown

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: 2.29 GB. The recommended download, model.safetensors, is 2.27 GB.

Q: What can I download here?

Hosted here: at least 8 listed files; full count and size unknown. Full repo upstream: 2.29 GB. The original release is at https://huggingface.co/Darmm/darmm-embedding-multilingual.

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-darmm-darmm-embedding-multilingual/safety on Hugging Bay.

Q: Will Darmm/darmm-embedding-multilingual 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.

Darmm

darmm-embedding-multilingual

Darmm/darmm-embedding-multilingual

Model details

sentence similarity and retrievalLicense: apache-2.0SHA-256 recorded for 9 of 13 filessafetensors

Content controls: not assessed.

The catalog lists this model for checking whether two sentences mean similar things. Catalog sources: license, cardMetadata.license, baseModel, 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-darmm-darmm-embedding-multilingual/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 13 listed · Hashes recorded. Date not recorded.

Selected downloadmodel.safetensors2.27 GB · 1 file Download · 2.27 GB (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 13 listed

Hashes recorded. Date not recorded.

File	Tamanho	SHA-256	Origem	Baixar
Weights
`model.safetensors` Default	2.27 GB	`59bfcf15…3a019af1` `59bfcf156b258c3f94a39d494357f8259f38eccf5158d1ebe3a1eecd3a019af1`	Hosted	Baixar
Tokenizer & config
`1_Pooling/config.json`	297 bytes	—	Upstream only	File metadata
`config.json`	698 bytes	`77474f40…b9f0f3f1` `77474f4007c1cebba6b84cb5783feb24b77ff298c8b454260b81268fb9f0f3f1`	Hosted	Baixar
`config_sentence_transformers.json`	171 bytes	`e828cbdf…82b3b6d6` `e828cbdf342962718aad2b3cdeb20b84cce34b7059a69da3e1c4fb1e82b3b6d6`	Hosted	Baixar
`sentence_bert_config.json`	53 bytes	`70f4448f…b0aa5a1f` `70f4448f31320443fe3557cacea5abf2dcc4915dda8c80646bec9f3bb0aa5a1f`	Hosted	Baixar
`sentencepiece.bpe.model`	5.07 MB	`cfc8146a…e0db2865` `cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865`	Upstream only	File metadata
`special_tokens_map.json`	964 bytes	`8c785abe…4cf10835` `8c785abebea9ae3257b61681b4e6fd8365ceafde980c21970d001e834cf10835`	Hosted	Baixar
`tokenizer.json`	17.1 MB	`c119aa9b…6550ffd7` `c119aa9bc83a5d76efbbc831b23e5790727c12fde474f6519dd96cde6550ffd7`	Hosted	Baixar
`tokenizer_config.json`	1.17 KB	`7e4c1cc8…4e7db2d4` `7e4c1cc848840aeccdd763458c18dd525eb0f795c992e00ebe9c28554e7db2d4`	Hosted	Baixar
`train_args.json`	229 bytes	—	Upstream only	File metadata
`modules.json`	349 bytes	`84e40c8e…7cf642cf` `84e40c8e006c9b1d6c122e02cba9b02458120b5fb0c87b746c41e0207cf642cf`	Hosted	Baixar
Docs
`.gitattributes`	1.57 KB	—	Upstream only	File metadata
`README.md`	6.2 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.

darmm-embedding-multilingual

Verificar um download

Cookies