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alt.freeweights.embed / use-cmlm-multilingual
From: sentence-transformers <huggingface.co/sentence-transformers>Newsgroups: alt.freeweights.embedSubject:

use-cmlm-multilingual

Date: 2026-11-15Commit: 736a295Signed: 2DC28CC7B26A283B ✓

Sentence similarity model with 472M parameters. Safetensors weights, 5.68 GB in all. Published by sentence-transformers under Apache-2.0.

472M params5.68GBuse-cmlm-multilingualsafetensorspermissive
FactsParams472MSize5.68 GBFormatssafetensorsTasksentence similarityLicenseApache-2.0From sourcepermissive
$ fw get sentence-transformers/use-cmlm-multilingual
# manifest sha256 7c42ab6a9abd… · 5.68 GB · 14 files
$ fw verify ./use-cmlm-multilingual sentence-transformers/use-cmlm-multilingual
From sourceHosted (signed)sentence-transformers/use-cmlm-multilingualLast check: 2026-11-15 03:25 UTC
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Overview

Size
5.68 GB
Weights
1.89 GB (safetensors)
Parameters
472M
Formats
safetensors
Task
sentence similarity
License
Apache-2.0 (permissive)
Files
14, each with a sha256
Publisher
sentence-transformers
Added
2026-11-15
Section
alt.freeweights.embed
Lineage

Original release from the publisher.

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BadgeHostLast checkResult
From sourcehuggingface.co2026-11-15 03:25 UTCpassed

Model card

From the publisher at commit 736a295. Shown as plain text with links; images open at the publisher.

use-cmlm-multilingual#

This is a pytorch version of the universal-sentence-encoder-cmlm/multilingual-base-br model. It can be used to map 109 languages to a shared vector space. As the model is based LaBSE, it perform quite comparable on downstream tasks.

Usage (Sentence-Transformers)#

Using this model becomes easy when you have sentence-transformers installed:

pip install -U sentence-transformers

Then you can use the model like this:

from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('sentence-transformers/use-cmlm-multilingual')
embeddings = model.encode(sentences)
print(embeddings)

Full Model Architecture#

SentenceTransformer(
  (0): Transformer({'max_seq_length': 256, 'do_lower_case': False}) with Transformer model: BertModel 
  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
  (2): Normalize()
)

Citing & Authors#

Have a look at universal-sentence-encoder-cmlm/multilingual-base-br for the respective publication that describes this model.

Files

14 files · 5.68 GBWeights 1.89 GB (safetensors). Sizes and sha256 from the signed manifest.
Hide all 14 files with their sha256
FileSizesha256
.gitattributes1.27 KB840744a6a8d0ca22f8f6228a6f19c750a47db069873a32eefba939e64c742b35
1_Pooling/config.json191 B6401a8eeaeca1f1fe2b1b46be987dcf2ee6085ec73f7d2263318ffc191dd91d3
README.md1.69 KBa55eedeb549854b040b2b1519d5e654719370221405b9d1a5dbc5fffe591f4cd
config.json804 Bb6bd83d561db8d2ccb7f44dafcd945e39bea16dc2819072ffb10adb45608b029
config_sentence_transformers.json122 Bb8c64b5cece00d8424b4896ea75b512b6008576088497609dfeb6bd63e6d36b8
model.safetensors1.89 GB9f6f97bd539c66196aeb1e1c6aa04932edc1bc9b6984184cdd8be12307602523
modules.json349 B84e40c8e006c9b1d6c122e02cba9b02458120b5fb0c87b746c41e0207cf642cf
pytorch_model.bin1.89 GBe7be21b1f0d10a8e5e7567b9e5b83a586a7dfe7704738bc0b362a0422aff93c4
sentence_bert_config.json53 Bfc1993fde0a95c24ec6c022539d41cf6e2f7c9721e5415d6fb6897472a9cd4b7
special_tokens_map.json112 B303df45a03609e4ead04bc3dc1536d0ab19b5358db685b6f3da123d05ec200e3
tf_model.h51.88 GBd751136aa0f06a298c6aa5a301ba9e884a6f57a817e079b6bd92f87fa8eae8df
tokenizer.json9.62 MBd09046654dc5151fc313613f16768b6ecc1e5e3bddbc9c8aca209a5f23fe3cd3
tokenizer_config.json411 B525a438411c082f87c38cf01bab0325b3f1428203508adc7d75a1d5cc67ed083
vocab.txt5.22 MB7453247caa2cf23116c1da332bec0cc1c9ef896b7803591a62ad2007b7a33c33
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
736a29561b pinned now2026-11-15 03:25 UTC14 files · 5.68 GB

Use it

$ fw get sentence-transformers/use-cmlm-multilingual
# manifest sha256 7c42ab6a9abd… · 5.68 GB · 14 files
$ fw verify ./use-cmlm-multilingual sentence-transformers/use-cmlm-multilingual
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/sentence-transformers/use-cmlm-multilingual.json --dir ./use-cmlm-multilingual $ python3 fw.py verify ./use-cmlm-multilingual ./sentence-transformers__use-cmlm-multilingual.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download sentence-transformers/use-cmlm-multilingual --revision 736a29561b4df04fc2d03bc7f6a574e4d0081b56 --local-dir ./use-cmlm-multilingual
transformersLoad the weights in Python.
import os os.environ["HF_ENDPOINT"] = "https://freeweights.allternit.com" from transformers import AutoModel, AutoTokenizer tok = AutoTokenizer.from_pretrained("sentence-transformers/use-cmlm-multilingual", revision="736a29561b4df04fc2d03bc7f6a574e4d0081b56") model = AutoModel.from_pretrained("sentence-transformers/use-cmlm-multilingual", revision="736a29561b4df04fc2d03bc7f6a574e4d0081b56", device_map="auto")
sentence-transformersEmbed text with sentence-transformers.
import os os.environ["HF_ENDPOINT"] = "https://freeweights.allternit.com" from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/use-cmlm-multilingual", revision="736a29561b4df04fc2d03bc7f6a574e4d0081b56") vectors = model.encode(["Hello"])
Run at home

License

Name
Apache License 2.0
Id
Apache-2.0
Class
Permissive
Redistribution
yes
Listing
Hosted (signed)
Decided
License as declared by the publisher. No person read it. 2026-11-15
Text in
README.md
Text sha256
a55eedeb549854b040b2b1519d5e654719370221405b9d1a5dbc5fffe591f4cd
Terms gate
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Read the license text

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Provenance

From: sentence-transformers <huggingface.co/sentence-transformers>Newsgroups: alt.freeweights.embedSubject: use-cmlm-multilingualDate: 2026-11-15Commit: 736a295Signed: 2DC28CC7B26A283B ✓
Upstream
sentence-transformers/use-cmlm-multilingual
Pinned commit
736a29561b4df04fc2d03bc7f6a574e4d0081b56
Manifest
use-cmlm-multilingual.json · .minisig
Manifest sha256
7c42ab6a9abd990dceeb37587c2b9b8954ea3657a8510da43e1efab04c883f76
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-15 03:25 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/sentence-transformers/use-cmlm-multilingual.json $ curl -O https://freeweights.allternit.com/manifests/sentence-transformers/use-cmlm-multilingual.json.minisig $ minisign -Vm use-cmlm-multilingual.json -P RWQ7KGqyx4zCLXtUFOqvfv8L3g+8fpKJ1FsuxPyOYMF+4KufbUxKq1Oq $ shasum -a 256 <file> # compare with the Files tab

A manifest whose signature fails must be rejected. A file whose size or sha256 does not match must be discarded. Verify a download

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Get it
Download
$ HF_ENDPOINT=https://freeweights.allternit.com hf download sentence-transformers/use-cmlm-multilingual
Open in Freeweights Studio

Pull, verify and run it in the Allternit app on Desktop, web or phone.

Signed manifest
minisign, key 2DC28CC7B26A283B. use-cmlm-multilingual.json. Provenance. Takedown history: none.
Source
huggingface.co/sentence-transformers/use-cmlm-multilingual

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