# rubert-tiny-toxicity by David Dale: Open-Weight Model Source: https://savrn.com/models/rubert-tiny-toxicity Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- ## Runs On What it takes to serve rubert-tiny-toxicity (12M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them. | Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits | | --- | --- | --- | --- | --- | --- | | 16-bit | 0.0 GB | 0.0 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | | 8-bit | 0.0 GB | 0.0 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | | 4-bit | 0.0 GB | 0.0 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the [SAVRN Index](https://savrn.com/ai-index/pricing/gpus), read Oct 24, 2026. [rubert-tiny-toxicity on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/rubert-tiny-toxicity/gpus) ## SAVRN's Notes on rubert-tiny-toxicity Moderating Russian-language comments is the job, and the model is small enough to live inside the comment pipeline itself. David Dale trained it to return five labels on a short informal text: non-toxic, insult, obscenity, threat, and dangerous. Twelve million parameters in three layers come to 94 MB of float32 weights, and our page rounds the 16-bit memory need to 0.0 GB. The cheapest listed setup, one MI300X at $1.85 an hour, is more card than this needs; it belongs on a spare slice of something already running. MIT terms permit commercial use, modification and redistribution provided the copyright and permission notices ride along, so a moderation vendor can ship it inside a product. Check the lineage, it is derived from cointegrated/rubert-tiny, and the 512-token context, which means long threads get split before scoring. It was last updated August 3, 2026, more than four years after its March 2022 release. SAVRN Research, 2026-09-18 ## Model Card By David Dale, published under mit, revision 5d37eff84486. This is the [cointegrated/rubert-tiny](https://huggingface.co/cointegrated/rubert-tiny) model fine-tuned for classification of toxicity and inappropriateness for short informal Russian texts, such as comments in social networks. The problem is formulated as multilabel classification with the following classes: - non-toxic: the text does NOT contain insults, obscenities, and threats, in the sense of the [OK ML Cup](https://cups.mail.ru/ru/tasks/1048) competition. - insult - obscenity - threat - dangerous: the text is inappropriate, in the sense of [Babakov et.al.](https://arxiv.org/abs/2103.05345), i.e. it can harm the reputation of the speaker. A text can be considered safe if it is BOTH non-toxic and NOT dangerous. ### Usage The function below estimates the probability that the text is either toxic OR dangerous: [Read the full model card (318 words)](https://savrn.com/models/rubert-tiny-toxicity/card) ## Configuration Architecture BertForSequenceClassification Context length (tokens) 512 Layers 3 Hidden size 312 Feed-forward size 600 Attention heads 12 Vocabulary size 29,564 Stored precision float32 Model type bert ## Identity and Version Repository cointegrated/rubert-tiny-toxicity Publisher David Dale Task Text classification Modality Text Library transformers Parameters 12M parameters Languages ru Revision 5d37eff844868e243467e4c38898bad46c271af2 First published 2022-03-02 Last updated 2026-08-03 ## Files and Weights 9 files, 95.0 MB in total. The weights are 2 files totalling 94.3 MB in bin, safetensors. Weights2 files · 94.3 MB Configuration2 files · 1.1 KB Tokenizer3 files · 709.5 KB Documentation1 file · 3.1 KB Repository1 file · 791 B Every file | File | Type | Size | SHA-256 | | --- | --- | --- | --- | | model.safetensors | Weights | 47.2 MB | e29f120dfe1f | | pytorch_model.bin | Weights | 47.2 MB | 3acf3c98b1f8 | | config.json | Configuration | 957 B | — | | special_tokens_map.json | Configuration | 112 B | — | | README.md | Documentation | 3.1 KB | — | | .gitattributes | Repository | 791 B | — | | tokenizer.json | Tokenizer | 468.0 KB | — | | tokenizer_config.json | Tokenizer | 377 B | — | | vocab.txt | Tokenizer | 241.1 KB | — | ## License and Download License mit Access Open weights, no gate Download size 94.3 MB [Download from David Dale](https://huggingface.co/cointegrated/rubert-tiny-toxicity) Released by David Dale through its official repository on Hugging Face. [Read the license](https://opensource.org/license/mit). ## Built From - Derived from cointegrated/rubert-tiny - Described by arXiv:2103.05345 ## Memory Requirements | Precision | Weights in memory | | --- | --- | | As published | 94.3 MB | | 16-bit | 0.0 GB | | 8-bit | 0.0 GB | | 4-bit | 0.0 GB | Weights only, from the published parameter count; the key-value cache and runtime add to this. ## Questions About rubert-tiny-toxicity ### How much GPU memory does rubert-tiny-toxicity need? About 0 GB at 16-bit and 0 GB at 4-bit: the weights (12M parameters) plus a working margin. A long context needs more. ### What is the cheapest GPU to run rubert-tiny-toxicity on? At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists. ### Can I use rubert-tiny-toxicity commercially? Yes. rubert-tiny-toxicity is released under MIT License. The MIT License is a short permissive license. It permits commercial use, modification and redistribution, provided the copyright notice and permission notice are included. ### What is rubert-tiny-toxicity's context length? 512 tokens, from the maximum position embeddings in its published configuration. ## Similar Models Model · Text classification ### [literary-bert-en-mini](https://savrn.com/models/literary-bert-en-mini) [ARTEM SUSLOV](https://savrn.com/model-publishers/susurofu) This model is BERT-mini (11.3M parameters) fine-tuned for sentence-level sentiment analysis of English literary text using ten ordered sentiment levels (1 = most negative, 10 = most positive). It is one of five student configurations trained on Gemma 4 31B-generated pseudo-labels for literary sentences. The training objective is cumulative-logit ordinal regression, rather than conventional three-class classification. 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