recogna-nlp/ptt5-base-summ-xlsum
summarization model by recogna-nlp
From the publisher
Model card & documentation
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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. This model was fine-tuned using the XL-Sum dataset, which is licensed under CC BY-NC-SA 4.0. As a result, this model is also distributed under the same license. If you intend to use this model for commercial purposes, you…
Read the full model card ↗ · Preview checked 2026-11-01T09:34:54.231Z
Inside the original model card — Document outline
- Portuguese T5 for Abstractive Summarization (PTT5 Summ)
- Introduction
- Available models
- Usage example
- Citation
- 📢 Licensing Notice
- Attribution (XL-SUM)
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Documentation belongs to its respective authors. Reported project/model license: cc-by-nc-sa-4.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
recogna-nlp/ptt5-base-summ-xlsum is a summarization model repository published by recogna-nlp on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- summarization
- Library
- transformers
- Recent downloads (30 days)
- 1,807
- Cumulative likes
- 17
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 222,903,552
- Architecture
- T5ForConditionalGeneration
- License
- cc-by-nc-sa-4.0
- Access
- Not gated by Hugging Face
- Created
- 2022-08-29T20:18:03.000Z
- Last modified
- 2025-07-10T17:33:15.000Z
Compatibility and lineage
Reported languages: pt
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:54:36.205Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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