alt.freeweights.vision / bert-multilingual-toxicity-classifier
From: textdetox <huggingface.co/textdetox>Newsgroups: alt.freeweights.visionSubject:

bert-multilingual-toxicity-classifier

Date: 2026-11-15Commit: 8fe5526Signed: 2DC28CC7B26A283B ✓

Text classification model with 178M parameters. Safetensors weights, 2.14 GB in all. Published by textdetox under OpenRAIL++-M (custom).

178M params2.14GBbert-multilingual-toxicity-classifiersafetensorscustom terms
FactsParams178MSize2.14 GBFormatssafetensorsTasktext classificationLicenseOpenRAIL++-M (custom)From sourcecustom termsread terms
# custom terms: read the license before you download
$ fw get textdetox/bert-multilingual-toxicity-classifier
# manifest sha256 53487b0785b7… · 2.14 GB · 13 files
$ fw verify ./bert-multilingual-toxicity-classifier textdetox/bert-multilingual-toxicity-classifier
From sourceHosted (signed)textdetox/bert-multilingual-toxicity-classifierLast check: 2026-11-15 02:33 UTC

Get help: custom fine-tune or private deploy. We review your setup before we quote.

Fine-tune of bert-base-multilingual-cased.

Overview

Size
2.14 GB
Weights
711 MB (safetensors)
Parameters
178M
Formats
safetensors
Task
text classification
License
OpenRAIL++-M (custom) (custom)
Files
13, each with a sha256
Publisher
textdetox
Added
2026-11-15
Section
alt.freeweights.vision
Lineage

Original release from the publisher.

Base model: google-bert/bert-base-multilingual-cased

Where these bytes come from
Publisher at the pinned commit→You

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Sources
BadgeHostLast checkResult
From sourcehuggingface.co2026-11-15 02:33 UTCpassed

Model card

From the publisher at commit 8fe5526. Shown as plain text with links; images open at the publisher.

Multilingual Toxicity Classifier for 15 Languages (2025)#

This is an instance of bert-base-multilingual-cased that was fine-tuned on binary toxicity classification task based on our updated (2025) dataset textdetox/multilingual_toxicity_dataset.

Now, the models covers 15 languages from various language families:

LanguageCodeF1 Score
Englishen0.9035
Russianru0.9224
Ukrainianuk0.9461
Germande0.5181
Spanishes0.7291
Arabicar0.5139
Amharicam0.6316
Hindihi0.7268
Chinesezh0.6703
Italianit0.6485
Frenchfr0.9125
Hinglishhin0.6850
Hebrewhe0.8686
Japaneseja0.8644
Tatartt0.6170

How to use#

import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained('textdetox/bert-multilingual-toxicity-classifier')
model = AutoModelForSequenceClassification.from_pretrained('textdetox/bert-multilingual-toxicity-classifier')

batch = tokenizer.encode("You are amazing!", return_tensors="pt")

output = model(batch)
# idx 0 for neutral, idx 1 for toxic

Citation#

The model is prepared for TextDetox 2025 Shared Task evaluation.

@inproceedings{dementieva2025overview,
  title={Overview of the Multilingual Text Detoxification Task at PAN 2025},
  author={Dementieva, Daryna and
      Protasov, Vitaly and
      Babakov, Nikolay and
      Rizwan, Naquee and
      Alimova, Ilseyar and
      Brune, Caroline and
      Konovalov, Vasily and
      Muti, Arianna and
      Liebeskind, Chaya and
      Litvak, Marina and
      Nozza, Debora, and
      Shah Khan, Shehryaar and
      Takeshita, Sotaro and
      Vanetik, Natalia and
      Ayele, Abinew Ali and
      Schneider, Frolian and
      Wang, Xintog and
      Yimam, Seid Muhie and
      Elnagar, Ashraf and
      Mukherjee, Animesh and
      Panchenko, Alexander},
    booktitle={Working Notes of CLEF 2025 -- Conference and Labs of the Evaluation Forum},
    editor={Guglielmo Faggioli and Nicola Ferro and Paolo Rosso and Damiano Spina},
    month =                    sep,
    publisher =                {CEUR-WS.org},
    series =                   {CEUR Workshop Proceedings},
    site =                     {Vienna, Austria},
    url =                      {https://ceur-ws.org/Vol-4038/paper_278.pdf},
    year =                     2025
}

Files

13 files · 2.14 GBWeights 711 MB (safetensors). Sizes and sha256 from the signed manifest.
Hide all 13 files with their sha256
FileSizesha256
.gitattributes1.52 KB11ad7efa24975ee4b0c3c3a38ed18737f0658a5f75a0a96787b576a78a023361
README.md3.07 KB6bbc9b3aaad9e6e2b7780504aca56a997e2a69d7b7f2598908b8d8cef21511e4
config.json946 Bee45aa7f0cd43a49401daea513a34be821fc6b998d2f2b75ae014a207ef22bb8
model.safetensors711 MBf83ff133690ade7432a57c34d49b3bd2d0c35e6475d38029c047f3dc9fd9de77
optimizer.pt1.42 GB8345d1b8f7fd9043ba83adf40cd2f08556d3b3296fa92114aea96f29a779c45e
rng_state.pth14.0 KB06e55bfc8723f269a626afca0be6f7def5753f3bb265436b94c5580b703cfcc7
scheduler.pt1.06 KB87b7588a7082272dcd9d16bc96af228034e76f91c693dad009c970adcc75ef43
special_tokens_map.json125 Bb6d346be366a7d1d48332dbc9fdf3bf8960b5d879522b7799ddba59e76237ee3
tokenizer.json2.92 MB4e8d2533b6e39afe137ac1ff84390ef303f71f9c257aab2df09f4c6a62d08bf3
tokenizer_config.json1.22 KB1c441dfe412d9d7e47c960029a48a0159c23a38a9ab41b465d90fb1f520d4ced
trainer_state.json4.01 KBa172a30ce8ad05d1a1eef17203c5cb229cfdf2773cb41ff0b3c169682c653dcc
training_args.bin5.37 KB13f45e1631cd3dd1a5f0e53516e815f1d3465687f77c62254f0f52a2dd71c017
vocab.txt996 KBfe0fda7c425b48c516fc8f160d594c8022a0808447475c1a7c6d6479763f310c
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
8fe5526e9c pinned now2026-11-15 02:33 UTC13 files · 2.14 GB

Use it

# custom terms: read the license before you download
$ fw get textdetox/bert-multilingual-toxicity-classifier
# manifest sha256 53487b0785b7… · 2.14 GB · 13 files
$ fw verify ./bert-multilingual-toxicity-classifier textdetox/bert-multilingual-toxicity-classifier
Terms that come with these files. OpenRAIL++-M: the use restrictions in Attachment A pass on to you and to anyone you share the model with. Keep a copy of the license with the files.
Custom license (custom). Read the license text first. Open this panel to show the commands once you accept its terms.
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/textdetox/bert-multilingual-toxicity-classifier.json --dir ./bert-multilingual-toxicity-classifier $ python3 fw.py verify ./bert-multilingual-toxicity-classifier ./textdetox__bert-multilingual-toxicity-classifier.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download textdetox/bert-multilingual-toxicity-classifier --revision 8fe5526e9c6b69cf1a615104a2ad037fb266c670 --local-dir ./bert-multilingual-toxicity-classifier

License

Name
CreativeML Open RAIL++-M
Id
LicenseRef-OpenRAIL++-M
Class
Custom terms
Redistribution
click-through
Listing
Hosted (signed)
Terms
OpenRAIL++-M: the use restrictions in Attachment A pass on to you and to anyone you share the model with. Keep a copy of the license with the files.
Decided
License as declared by the publisher. No person read it. 2026-11-15
Text in
README.md
Text sha256
6bbc9b3aaad9e6e2b7780504aca56a997e2a69d7b7f2598908b8d8cef21511e4
Terms gate
Yes. The commands stay folded until you open them after reading the license.

Read the license text

Licenses are checked against the license table. A custom license passes only after a person reads it.

Provenance

From: textdetox <huggingface.co/textdetox>Newsgroups: alt.freeweights.visionSubject: bert-multilingual-toxicity-classifierDate: 2026-11-15Commit: 8fe5526Signed: 2DC28CC7B26A283B ✓
Upstream
textdetox/bert-multilingual-toxicity-classifier
Pinned commit
8fe5526e9c6b69cf1a615104a2ad037fb266c670
Manifest
bert-multilingual-toxicity-classifier.json · .minisig
Manifest sha256
53487b0785b752a4dbc932c72c6d987103e995b95d25d2279013c9e90ca3965f
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-15 02:33 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/textdetox/bert-multilingual-toxicity-classifier.json $ curl -O https://freeweights.allternit.com/manifests/textdetox/bert-multilingual-toxicity-classifier.json.minisig $ minisign -Vm bert-multilingual-toxicity-classifier.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

Model tree

Parent

google-bert/bert-base-multilingual-cased · this model is a finetune of it

1 model in the catalog name this one as their parent.

Quantizations
1
Get it
Read license, then download
$ HF_ENDPOINT=https://freeweights.allternit.com hf download textdetox/bert-multilingual-toxicity-classifier
Open in Freeweights Studio

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

Signed manifest
minisign, key 2DC28CC7B26A283B. bert-multilingual-toxicity-classifier.json. Provenance. Takedown history: none.

Variants

1 quantized or adapter build of bert-multilingual-toxicity-classifier. Each has its own license check and page.

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