multilingual-e5-small safetensors download | Hugging Bay

Q: What is this model?

intfloat/multilingual-e5-small is an embedding model for sentence similarity and retrieval published by intfloat, added to Hugging Bay Jun 29, 2026. Model from Hugging Face for sentence similarity: intfloat/multilingual-e5-small · 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: 8 files, 475.7 MB. Full repo upstream: 2.28 GB. The recommended download, model.safetensors, is 470.6 MB.

Q: What can I download here?

Hosted here: 8 files, 475.7 MB. Full repo upstream: 2.28 GB. The original release is at https://huggingface.co/intfloat/multilingual-e5-small.

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-intfloat-multilingual-e5-small/safety on Hugging Bay.

Q: Will intfloat/multilingual-e5-small 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.

intfloat

multilingual-e5-small

Can I run multilingual-e5-small 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.

multilingual-e5-small 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: 1a55775f53449dac10a2bcbc312469fac40b96d53198c407081a831f81c98477. 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 2026-04-02 at the model source. Popularity counters are source-reported, not measured by Hugging Bay. Availability checked 2026-10-22.

intfloat/multilingual-e5-small

Model details

sentence similarity and retrievalLicense: mitSHA-256 recorded for 42 of 43 filessafetensors · ONNX · BIN

Content controls: not assessed.

The catalog lists this model for checking whether two sentences mean similar things. Catalog sources: license, cardMetadata.license, 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-intfloat-multilingual-e5-small/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 43 listed · Hashes recorded. Date not recorded.

Selected downloadmodel.safetensors471 MB · 1 file Download · 471 MB (1 file)

Open-file help

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Check your download →

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

8 hosted of 43 listed

Hashes recorded. Date not recorded.

File	大小	SHA-256	来源	下载
Weights
`model.safetensors` Default	470.6 MB	`1a55775f…81c98477` `1a55775f53449dac10a2bcbc312469fac40b96d53198c407081a831f81c98477`	Hosted	下载
`onnx/model.onnx`	470.3 MB	`ca456c06…a6bc8665` `ca456c06b3a9505ddfd9131408916dd79290368331e7d76bb621f1cba6bc8665`	Upstream only	File metadata
`onnx/model_O4.onnx`	235.1 MB	`4654c156…0e3205b0` `4654c156f3e4171abc9c716cdb771bf9116455d15ac1aab364aeeede0e3205b0`	Upstream only	File metadata
`onnx/model_qint8_avx512_vnni.onnx`	118.3 MB	`dd476dd0…c48a2d88` `dd476dd0c2514e9b9be83aeb3853fac0763e0bdf4a71645407587d77c48a2d88`	Upstream only	File metadata
`openvino/openvino_model.bin`	470 MB	`22f5a10e…bc6cf232` `22f5a10ec005a1606ec42758dedd52b59dfcb6e3d85de0b6b86946d0bc6cf232`	Upstream only	File metadata
`pytorch_model.bin`	470.7 MB	`f0ccb64a…49c51167` `f0ccb64a2edc689fce7b1895f25146740e4075c3da28c8d0e672a8ba49c51167`	Upstream only	File metadata
Tokenizer & config
`.eval_results/ArguAna.yaml`	575 bytes	`53c1be5a…9092371c` `53c1be5a451d915708a64756b626b7a8772ce8a785d6f4be5a7652709092371c`	Upstream only	File metadata
`.eval_results/BrightAopsRetrieval.yaml`	641 bytes	`6027ed10…3651e599` `6027ed1058e852c2c0a9d34fbce4c10d18252681de802a6082282f363651e599`	Upstream only	File metadata
`.eval_results/BrightBiologyLongRetrieval.yaml`	651 bytes	`f4ebcfd6…da75b439` `f4ebcfd606c3f1283907d8b4b434fa32848e0e4a122556e701919a95da75b439`	Upstream only	File metadata
`.eval_results/BrightBiologyRetrieval.yaml`	647 bytes	`a68fca02…010f15d4` `a68fca027604de4c877e7d86b1858c5025c64029c1cddfd351e5d05e010f15d4`	Upstream only	File metadata
`.eval_results/BrightEarthScienceLongRetrieval.yaml`	663 bytes	`4256206c…52fb9a68` `4256206ca8f244b911a94858b8a7d32854fcad90f701e814bfa808d252fb9a68`	Upstream only	File metadata
`.eval_results/BrightEarthScienceRetrieval.yaml`	659 bytes	`5dd5cae9…b274209b` `5dd5cae91c338408a31ba5a5b824edb36e0d3b0d913e38ef678240deb274209b`	Upstream only	File metadata
`.eval_results/BrightEconomicsLongRetrieval.yaml`	655 bytes	`891ee9ad…2f5e9f4b` `891ee9ad5db6ef7708cc2f73f56bd498ba8ea4ad4b6e061eb33472642f5e9f4b`	Upstream only	File metadata
`.eval_results/BrightEconomicsRetrieval.yaml`	651 bytes	`7f0c3385…1f7b51d9` `7f0c33852f1da36d56e041479ef085c0ef53ecf786bbe972fe4a7e4f1f7b51d9`	Upstream only	File metadata
`.eval_results/BrightLeetcodeRetrieval.yaml`	651 bytes	`7d163f44…c5123823` `7d163f441cf3f929d684af2c9c9933e1d6090b25926d18f467e1b168c5123823`	Upstream only	File metadata
`.eval_results/BrightPonyLongRetrieval.yaml`	645 bytes	`502c6c13…6496e0ab` `502c6c13dd57ae95f4eda6f19f88550b971e7fdb46f13b2873c65d796496e0ab`	Upstream only	File metadata
`.eval_results/BrightPonyRetrieval.yaml`	641 bytes	`5b99465c…5155a72c` `5b99465cbd9eb7df09b34dde9895f478a88abaa3b5ff4474b49a5d0f5155a72c`	Upstream only	File metadata
`.eval_results/BrightPsychologyLongRetrieval.yaml`	655 bytes	`4ad33f80…f877dddd` `4ad33f80d26bb613e2def7584455f975c7466cdf61335348cf2159fff877dddd`	Upstream only	File metadata
`.eval_results/BrightPsychologyRetrieval.yaml`	653 bytes	`fd43e8a6…6d12a137` `fd43e8a64eb654e8773aa3ecbc947026edf42f92c629bdd9da87b8b56d12a137`	Upstream only	File metadata
`.eval_results/BrightRoboticsLongRetrieval.yaml`	653 bytes	`9dcdf929…435c64a3` `9dcdf92946535dcf14304cb906cdec0d9db7bd4412a4a0158103cdb1435c64a3`	Upstream only	File metadata
`.eval_results/BrightRoboticsRetrieval.yaml`	647 bytes	`71fdf009…11b82f4f` `71fdf00946b422675b53f598a22db9d3353cee4c4a153103f7cf7c2011b82f4f`	Upstream only	File metadata
`.eval_results/BrightStackoverflowLongRetrieval.yaml`	665 bytes	`d7e90b11…10deadf2` `d7e90b118eae1abb7b55579913a8da02cf1d337b032c0c998777325910deadf2`	Upstream only	File metadata
`.eval_results/BrightStackoverflowRetrieval.yaml`	659 bytes	`9dc86823…840a5aae` `9dc868231ebc0a78b94b3f4e681d476d67fb9e9c630626832e0af21e840a5aae`	Upstream only	File metadata
`.eval_results/BrightSustainableLivingLongRetrieval.yaml`	673 bytes	`7ddd8840…a6d6a45a` `7ddd8840466a84effef1df193ef79e1a6457567925b4e3b28b034832a6d6a45a`	Upstream only	File metadata
`.eval_results/BrightSustainableLivingRetrieval.yaml`	667 bytes	`91644839…1f859c28` `91644839f8ef7ebd5844b2f8ce6719f63af14656e2acef2403895c8b1f859c28`	Upstream only	File metadata
`.eval_results/BrightTheoremQAQuestionsRetrieval.yaml`	669 bytes	`00408cfa…377d797c` `00408cfa91d8677d9c6eefd98d37786d4a6a03b2a8cbb9c8d8364633377d797c`	Upstream only	File metadata
`.eval_results/BrightTheoremQATheoremsRetrieval.yaml`	667 bytes	`ecb1a69a…cf5251f1` `ecb1a69acecd2cb165ff9cd94aec3da58c63fcecd8972258b446f0dbcf5251f1`	Upstream only	File metadata
`1_Pooling/config.json`	200 bytes	`987f7a67…aebb12a0` `987f7a67a38fa564c849bb5d277c52ab9088a84368fc0be31a354125aebb12a0`	Hosted	下载
`config.json`	655 bytes	`69137736…81abf959` `69137736cab8b8903a07fe8afaafdda25aac55415a12a55d1bffa9f581abf959`	Hosted	下载
`modules.json`	387 bytes	`c6e29747…5f902b04` `c6e29747481e8b5dd2b58401966aeac910de39092f90cda9a704b1545f902b04`	Hosted	下载
`onnx/config.json`	653 bytes	`bbb7c133…7545a6b6` `bbb7c1333fc4b3e27fbc9cd5d2070aabcc1d4dfb99917c3633e772f97545a6b6`	Upstream only	File metadata
`onnx/sentencepiece.bpe.model`	5.07 MB	`cfc8146a…e0db2865` `cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865`	Upstream only	File metadata
`onnx/special_tokens_map.json`	167 bytes	`d05497f1…1afc07a7` `d05497f1da52c5e09554c0cd874037a083e1dc1b9cfd48034d1c717f1afc07a7`	Upstream only	File metadata
`onnx/tokenizer.json`	17.1 MB	`0b44a9d7…ebdf4c39` `0b44a9d7b51c3c62626640cda0e2c2f70fdacdc25bbbd68038369d14ebdf4c39`	Upstream only	File metadata
`onnx/tokenizer_config.json`	443 bytes	`a1d6bc87…ff53425b` `a1d6bc8734a6f635dc158508bef000f8e2e5a759c7d92f984b2c86e5ff53425b`	Upstream only	File metadata
`openvino/openvino_model.xml`	363.4 KB	—	Upstream only	File metadata
`sentence_bert_config.json`	57 bytes	`948201d8…ee986529` `948201d8329907aae938fa62f9ceeed53f5694dacc2b87b9f3b78b37ee986529`	Hosted	下载
`sentencepiece.bpe.model`	5.07 MB	`cfc8146a…e0db2865` `cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865`	Hosted	下载
`special_tokens_map.json`	167 bytes	`d05497f1…1afc07a7` `d05497f1da52c5e09554c0cd874037a083e1dc1b9cfd48034d1c717f1afc07a7`	Hosted	下载
`tokenizer.json`	17.1 MB	`0b44a9d7…ebdf4c39` `0b44a9d7b51c3c62626640cda0e2c2f70fdacdc25bbbd68038369d14ebdf4c39`	Upstream only	File metadata
`tokenizer_config.json`	443 bytes	`a1d6bc87…ff53425b` `a1d6bc8734a6f635dc158508bef000f8e2e5a759c7d92f984b2c86e5ff53425b`	Hosted	下载
Docs
`.gitattributes`	1.57 KB	`34448b82…e012a930` `34448b82c17d60fec9b65b1f093c115ddbaadc04beb1b0140b6bfed2e012a930`	Upstream only	File metadata
`README.md`	497.5 KB	`0038de97…241e9c1c` `0038de97aee16258cecbad7ffda4b4febd6953e747a00e0ddbc8e6ed241e9c1c`	Upstream only	File metadata

检查下载文件

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.

multilingual-e5-small

Can I run multilingual-e5-small on my computer?

检查下载文件

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