Nepali_Embedding_Model safetensors download | Hugging Bay

Q: What is this model?

universalml/Nepali_Embedding_Model is an embedding model for sentence similarity and retrieval published by universalml, added to Hugging Bay Jun 30, 2026. Model from Hugging Face: universalml/Nepali_Embedding_Model

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. The full repository size is not recorded. The recommended download, model.safetensors, is 2.24 GB.

Q: What can I download here?

Hosted here: at least 8 listed files; full count and size unknown. Full repo upstream: unknown. The original release is at https://huggingface.co/universalml/Nepali_Embedding_Model.

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-universalml-nepali-embedding-model/safety on Hugging Bay.

Q: Will universalml/Nepali_Embedding_Model 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.

universalml

Nepali_Embedding_Model

universalml/Nepali_Embedding_Model

Model details

sentence similarity and retrievalLicense: apache-2.0SHA-256 recorded for 10 of 11 filessafetensors

Content controls: not assessed.

Listed for comparing sentences; for developers building text similarity tools. Catalog sources: license, task.

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-universalml-nepali-embedding-model/model.safetensors",
    "model.safetensors",
)

Other ways

Run it on your computerOpen in Hugging Bay appSend to a computerApp links support one GGUF file.

8 hosted of 11 listed · Hashes recorded. Date not recorded.

Selected downloadmodel.safetensors2.24 GB · 1 file Download · 2.24 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 11 listed

Hashes recorded. Date not recorded.

File	Taille	SHA-256	Source	Télécharger
Weights
`model.safetensors` Default	2.24 GB	`9896ca3a…f1549cd0` `9896ca3aa5099620001a7eba78c5dbf064c5b531ca15184e4913f40ef1549cd0`	Hosted	Télécharger
Tokenizer & config
`1_Pooling/config.json`	297 bytes	`4e103b8e…907b3822` `4e103b8e2a31573ea88570523c2db4f13d34e09a26333e8a889268ed907b3822`	Upstream only	File metadata
`config.json`	725 bytes	`2145eef2…630da88d` `2145eef200a6aa3014fa8c553ff7bbdcd35611f27d4f05cf8648f54d630da88d`	Hosted	Télécharger
`config_sentence_transformers.json`	201 bytes	`f68c198a…c626332d` `f68c198aa2a236ce20f13c86cac99867a16d0578ec7c37517be93055c626332d`	Hosted	Télécharger
`sentence_bert_config.json`	53 bytes	`ec8e29d6…5a8d0d51` `ec8e29d6dcb61b611b7d3fdd2982c4524e6ad985959fa7194eacfb655a8d0d51`	Hosted	Télécharger
`special_tokens_map.json`	964 bytes	`8c785abe…4cf10835` `8c785abebea9ae3257b61681b4e6fd8365ceafde980c21970d001e834cf10835`	Hosted	Télécharger
`tokenizer.json`	17.1 MB	`883b0371…0f137085` `883b037111086fd4dfebbbc9b7cee11e1517b5e0c0514879478661440f137085`	Hosted	Télécharger
`tokenizer_config.json`	1.18 KB	`49f06d15…489f8175` `49f06d15a18f81855c338f8ab6241ca2e502a65b62968be69b74f094489f8175`	Hosted	Télécharger
`modules.json`	349 bytes	`84e40c8e…7cf642cf` `84e40c8e006c9b1d6c122e02cba9b02458120b5fb0c87b746c41e0207cf642cf`	Hosted	Télécharger
Docs
`README.md`	4.18 KB	`5e81cfef…c55bf8e6` `5e81cfef24657f00d51f68b5dea3b9d3b3c4ad92aef72264d8ac6188c55bf8e6`	Upstream only	File metadata
`.gitattributes`	0 bytes	—	Upstream only	File metadata

Vérifier un téléchargement

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.

Nepali_Embedding_Model

Vérifier un téléchargement

Cookies