# rut5-base-summ by Dmitry Balobin: Open-Weight Model Source: https://savrn.com/models/rut5-base-summ Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- ## Runs On What it takes to serve rut5-base-summ (223M 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 | 0.4 GB | 0.5 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 | 0.2 GB | 0.3 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 | 0.1 GB | 0.1 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 22, 2026. [rut5-base-summ on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/rut5-base-summ/gpus) ## Model Card Finetuned ai-forever/ruT5-base for text and dialogue summarization. All 'train' subsets was concatenated and shuffled with seed 1000 - 7. Train subset = 155678 rows. Evaluation on 10% of concatenated 'validation' subsets = 1458 rows. See WandB logs. See report at REPORT WIP. Excerpt from the card by Dmitry Balobin. ## Configuration Architecture T5ForConditionalGeneration Vocabulary size 32,128 Stored precision float32 Model type t5 ## Identity and Version Repository d0rj/rut5-base-summ Publisher Dmitry Balobin Task Summarization Modality Text Library transformers Parameters 223M parameters Languages ru, en Revision 118f9052c668b37cf07d3c1839d4416f8972821a First published 2023-06-21 Last updated 2023-10-05 ## Files and Weights 15 files, 1.8 GB in total. The weights are 6 files totalling 1.8 GB in bin, pt, pth, safetensors. Weights6 files · 1.8 GB Configuration4 files · 135.7 KB Tokenizer3 files · 3.6 MB Documentation1 file · 13.4 KB Repository1 file · 1.5 KB Every file | File | Type | Size | SHA-256 | | --- | --- | --- | --- | | model.safetensors | Weights | 891.6 MB | fcce1e8d3ad4 | | optimizer.pt | Weights | 2.1 MB | dd9ff5210e46 | | pytorch_model.bin | Weights | 891.7 MB | bafa4d4fad62 | | rng_state.pth | Weights | 14.5 KB | 58808399e58d | | scheduler.pt | Weights | 623 B | c947b15af77a | | training_args.bin | Weights | 4.0 KB | 79b3ae325469 | | config.json | Configuration | 1.6 KB | — | | generation_config.json | Configuration | 206 B | — | | special_tokens_map.json | Configuration | 2.2 KB | — | | trainer_state.json | Configuration | 131.7 KB | — | | README.md | Documentation | 13.4 KB | — | | .gitattributes | Repository | 1.5 KB | — | | spiece.model | Tokenizer | 1.0 MB | 7a4eb8701144 | | tokenizer.json | Tokenizer | 2.6 MB | — | | tokenizer_config.json | Tokenizer | 2.4 KB | — | ## License and Download License Not stated by the source Access Open weights, no gate Download size 1.8 GB [Download from Dmitry Balobin](https://huggingface.co/d0rj/rut5-base-summ) Released by Dmitry Balobin through its official repository on Hugging Face. ## Built From - Trained on (disclosed) GEM/wiki_lingua - Trained on (disclosed) IlyaGusev/gazeta - Trained on (disclosed) d0rj/samsum-ru - Trained on (disclosed) mlsum - Trained on (disclosed) rcp-meetings/rudialogsum_v2 - Trained on (disclosed) zjkarina/matreshka ## Evaluations Each result is shown as reported, with the conditions its reporter stated. None is a SAVRN measurement. A comparison lines two results up only when their configuration, unit and setup are all stated and identical. | Benchmark | Conditions | Result | Reported by | Revision | Date | | --- | --- | --- | --- | --- | --- | | samsum | Configuration samsumTask SummarizationMetric ROUGE-1Comparison conditions not established | 28.8694 | [d0rj](https://huggingface.co/d0rj/rut5-base-summ) Publisher reported | Evaluated revision not stated | — | | samsum | Configuration samsumTask SummarizationMetric ROUGE-2Comparison conditions not established | 8.4686 | [d0rj](https://huggingface.co/d0rj/rut5-base-summ) Publisher reported | Evaluated revision not stated | — | | samsum | Configuration samsumTask SummarizationMetric ROUGE-LComparison conditions not established | 24.2357 | [d0rj](https://huggingface.co/d0rj/rut5-base-summ) Publisher reported | Evaluated revision not stated | — | | samsum | Configuration samsumTask SummarizationMetric ROUGE-LSUMComparison conditions not established | 25.8543 | [d0rj](https://huggingface.co/d0rj/rut5-base-summ) Publisher reported | Evaluated revision not stated | — | | samsum | Configuration samsumTask SummarizationMetric gen_lenComparison conditions not established | 27.5543 | [d0rj](https://huggingface.co/d0rj/rut5-base-summ) Publisher reported | Evaluated revision not stated | — | | samsum | Configuration samsumTask SummarizationMetric lossComparison conditions not established | 3.2456 | [d0rj](https://huggingface.co/d0rj/rut5-base-summ) Publisher reported | Evaluated revision not stated | — | | xsum | Configuration defaultTask SummarizationMetric ROUGE-1Comparison conditions not established | 16.1279 | [d0rj](https://huggingface.co/d0rj/rut5-base-summ) Publisher reported | Evaluated revision not stated | — | | xsum | Configuration defaultTask SummarizationMetric ROUGE-2Comparison conditions not established | 2.1128 | [d0rj](https://huggingface.co/d0rj/rut5-base-summ) Publisher reported | Evaluated revision not stated | — | | xsum | Configuration defaultTask SummarizationMetric ROUGE-LComparison conditions not established | 12.2033 | [d0rj](https://huggingface.co/d0rj/rut5-base-summ) Publisher reported | Evaluated revision not stated | — | | xsum | Configuration defaultTask SummarizationMetric ROUGE-LSUMComparison conditions not established | 12.4127 | [d0rj](https://huggingface.co/d0rj/rut5-base-summ) Publisher reported | Evaluated revision not stated | — | | xsum | Configuration defaultTask SummarizationMetric gen_lenComparison conditions not established | 39.2258 | [d0rj](https://huggingface.co/d0rj/rut5-base-summ) Publisher reported | Evaluated revision not stated | — | | xsum | Configuration defaultTask SummarizationMetric lossComparison conditions not established | 4.57575 | [d0rj](https://huggingface.co/d0rj/rut5-base-summ) Publisher reported | Evaluated revision not stated | — | ## Memory Requirements | Precision | Weights in memory | | --- | --- | | As published | 1.8 GB | | 16-bit | 0.4 GB | | 8-bit | 0.2 GB | | 4-bit | 0.1 GB | Weights only, from the published parameter count; the key-value cache and runtime add to this. ## Questions About rut5-base-summ ### How much GPU memory does rut5-base-summ need? About 0.5 GB at 16-bit and 0.1 GB at 4-bit: the weights (223M parameters) plus a working margin. A long context needs more. ### What is the cheapest GPU to run rut5-base-summ 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. ## Similar Models Model · Summarization ### [T5-base-10K-summarization](https://savrn.com/models/t5-base-10k-summarization) [Yatharth Sant](https://savrn.com/model-publishers/yatharth97) This model is a fine-tuned version of Google's T5-Base model tailored for summarizing financial 10K report sections. T5-Base-10K-Summarization is optimized to condense lengthy 10K reports into manageable summaries, enabling quick insights into financial data and trends. Ideal for use by financial analysts and regulatory agencies needing rapid insights from 10K reports. It may not be suited for summarizing non-financial documents or informal texts. 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Open weights mit 223M parameters transformers [View model](https://savrn.com/models/ptt5-base-summ) Model · Summarization ### [ptt5-base-summ-xlsum](https://savrn.com/models/ptt5-base-summ-xlsum) [Recogna NLP](https://savrn.com/model-publishers/recogna-nlp) PTT5 Summ is a fine-tuned PTT5 model to perform Abstractive Summarization in Brazilian Portuguese texts. This model was fine-tuned on the datasets: RecognaSumm, WikiLingua, XL-Sum, TeMário.pdf) and CSTNews. For further information, please go to PTT5 Summ repository. author="Paiola, Pedro H. and de Rosa, Gustavo H. and Papa, Jo{\~a}o P.", editor="Xavier-Junior, Jo{\~a}o Carlos and Rios, Ricardo Ara{\'u}jo", title="Deep Learning-Based Abstractive Summarization for Brazilian Portuguese Texts", booktitle="BRACIS 2022: Intelligent Systems", year="2022", publisher="Springer International Publishing", address="Cham", pages="479--493", isbn="978-3-031-21689-3"} This model was fine-tuned using the… Open weights cc-by-nc-sa-4.0 223M parameters transformers [View model](https://savrn.com/models/ptt5-base-summ-xlsum) Model · Summarization ### [led-base-book-summary](https://savrn.com/models/led-base-book-summary) [Peter Szemraj](https://savrn.com/model-publishers/pszemraj) The Longformer Encoder-Decoder (LED) for Narrative-Esque Long Text Summarization is a model I fine-tuned from allenai/led-base-16384 to condense extensive technical, academic, and narrative content in a fairly generalizable way. - Ideal for summarizing long narratives, articles, papers, textbooks, and other documents. - the sparknotes-esque style leads to 'explanations' in the summarized content, offering insightful output. 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Open weights 124M parameters 1,026 tokens transformers [View model](https://savrn.com/models/kobart-summary-v3) ## Dmitry Balobin [All models and datasets](https://savrn.com/model-publishers/d0rj) ## Versions - [118f9052c668](https://savrn.com/models/rut5-base-summ/versions/118f9052c668) · current 2026-09-18 ## Explore More - [All summarization models](https://savrn.com/models/tasks/summarization) - [Model comparisons](https://savrn.com/models/comparisons) - [The model directory](https://savrn.com/models) - [Open model prices by host](https://savrn.com/ai-index/pricing/open-models) ## Source - Repository metadata, read 2026-10-21. - [Hugging Face record](https://huggingface.co/d0rj/rut5-base-summ) - [How the hub is built](https://savrn.com/model-hub/methodology)