mmlw-e5-large safetensors download (2.24 GB) | Hugging Bay

Q: What is this model?

sdadas/mmlw-e5-large is an embedding model for sentence similarity and retrieval published by sdadas, added to Hugging Bay Jun 30, 2026. Model from Hugging Face: sdadas/mmlw-e5-large

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/sdadas/mmlw-e5-large.

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-sdadas-mmlw-e5-large/safety on Hugging Bay.

Q: Will sdadas/mmlw-e5-large 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.

sdadas

mmlw-e5-large

Can I run mmlw-e5-large 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.

mmlw-e5-large is an embedding model for sentence similarity and retrieval. Model weights are learned parameters; a runtime loads them. Hosting files does not prove that a complete model runs.

As of the availability check on 2026-10-22.

Recorded SHA-256 for model.safetensors: fce612437e77e406173a296ef5d1792f8ecf1edd6ee63348e59d9671df190ee7. File evidence · Machine-readable facts · Run evidence and any recorded receipts · Proof Lab measurement policy. A checksum verifies byte identity, not safety; this answer asserts no measured runtime result.

Updated 2026-10-21 · Page text: As of 2026-10-21 · Content revision

Model metadata: As of 2026-09-22 at the model source. Popularity counters are source-reported, not measured by Hugging Bay. Availability checked 2026-10-22.

sdadas/mmlw-e5-large

Model details

sentence similarity and retrievalLicense: apache-2.0SHA-256 recorded for 11 of 13 filessafetensors · BIN

Content controls: not assessed.

The catalog lists this model for checking whether two sentences mean similar things. 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-sdadas-mmlw-e5-large/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.safetensors2.24 GB · 1 file Download · 2.24 GB (1 file)

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Check your download →

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

8 hosted of 13 listed

Hashes recorded. Date not recorded.

File	Taille	SHA-256	Source	Télécharger
Weights
`model.safetensors` Default	2.24 GB	`fce61243…df190ee7` `fce612437e77e406173a296ef5d1792f8ecf1edd6ee63348e59d9671df190ee7`	Hosted	Télécharger
`pytorch_model.bin`	0 bytes	—	Upstream only	File metadata
Tokenizer & config
`1_Pooling/config.json`	191 bytes	`e54c164a…e0597352` `e54c164a07274f2eb45bb724f54a79d1efcc90c41573887cd9a29aeee0597352`	Upstream only	File metadata
`config.json`	716 bytes	`508561bf…b12164d8` `508561bf340f7498ae1cfe0aafb9d1895c6c15bd1b8394c096a1f42bb12164d8`	Hosted	Télécharger
`config_sentence_transformers.json`	127 bytes	`229131b8…df347e9d` `229131b882edf5a9ff44fbb1a0b4a3e2c5ff3ec922e2cf701415319adf347e9d`	Hosted	Télécharger
`modules.json`	229 bytes	`8f4b264b…b3145460` `8f4b264b80206c830bebbdcae377e137925650a433b689343a63bdc9b3145460`	Hosted	Télécharger
`sentence_bert_config.json`	53 bytes	`ec8e29d6…5a8d0d51` `ec8e29d6dcb61b611b7d3fdd2982c4524e6ad985959fa7194eacfb655a8d0d51`	Hosted	Télécharger
`sentencepiece.bpe.model`	5.07 MB	`cfc8146a…e0db2865` `cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865`	Upstream only	File metadata
`tokenizer.json`	17.1 MB	`46afe88d…1891d0a7` `46afe88da5fd71bdbab5cfab5e84c1adce59c246ea5f9341bbecef061891d0a7`	Hosted	Télécharger
`tokenizer_config.json`	418 bytes	`efb5c0d0…3216da15` `efb5c0d09722e5fe59a462cd2a9976ee216d55b037597d997cd3fe833216da15`	Hosted	Télécharger
`special_tokens_map.json`	280 bytes	`06e405a3…6318067f` `06e405a36dfe4b9604f484f6a1e619af1a7f7d09e34a8555eb0b77b66318067f`	Hosted	Télécharger
Docs
`README.md`	30.7 KB	`ac32af08…f6f35d28` `ac32af083227e96ea5fd9ccea7a3beb2b8df472bdc8b00c9d5e5af11f6f35d28`	Upstream only	File metadata
`.gitattributes`	0 bytes	—	Upstream only	File metadata

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shasum -a 256 -- 'model.safetensors'

Linux

sha256sum -- 'model.safetensors'

Windows

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

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mmlw-e5-large

Can I run mmlw-e5-large on my computer?

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