Text Classification
Transformers
PyTorch
Safetensors
Serbian
electra
serbian
sentiment-analysis
wordnet
sentiwordnet
lexicon-induction
Instructions to use Tanor/BERTicSENTPOS4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tanor/BERTicSENTPOS4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tanor/BERTicSENTPOS4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tanor/BERTicSENTPOS4") model = AutoModelForSequenceClassification.from_pretrained("Tanor/BERTicSENTPOS4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Declare model license and document upstream attribution
Browse filesApply maintainer-approved family license: apache-2.0. Add the full LICENSE and NOTICE; document upstream provenance, declaration history and unresolved exact SrpWN release permissions. Only README.md, LICENSE and NOTICE are changed. Model artifacts and visibility are unchanged.
LICENSE
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| 1 |
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Tanor/BERTicSENTPOS4
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| 2 |
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Model and documentation license: Apache License 2.0
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| 3 |
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License text: LICENSE
|
| 4 |
+
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| 5 |
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Original base model: classla/bcms-bertic
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| 6 |
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Upstream attribution: Nikola Ljubešić and Davor Lauc; published by CLASSLA
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| 7 |
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Upstream model card: https://huggingface.co/classla/bcms-bertic/blob/5db9755d6152ec6403c0201223e4848bd1b98a48/README.md
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| 8 |
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Upstream license declaration: apache-2.0
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The upstream card revision above is the licensing-source snapshot inspected on
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23 September 2026; it is not asserted to be the original training revision.
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| 11 |
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Base-model reference:
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| 13 |
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Ljubešić, Nikola and Lauc, Davor (2021). BERTić - The Transformer Language Model for Bosnian, Croatian, Montenegrin and Serbian. https://aclanthology.org/2021.bsnlp-1.5/
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| 14 |
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Fine-tuning and release: Tanor (Saša Petalinkar)
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| 16 |
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This model adapts the base-model family for binary POS classification of
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| 17 |
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Serbian WordNet synset glosses using expansion iteration T4.
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| 18 |
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Documented fine-tuned weights revision: d5dda358196a587e0ab17a00a2da17f996c881a3
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| 19 |
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Research reference:
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| 21 |
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Saša Petalinkar, Ranka M. Stanković, and Milica Ikonić Nešić (2025).
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| 22 |
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Comparative analysis of methods for creating a sentiment lexicon of the Serbian WordNet.
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The Electronic Library, 43(4), 547–577.
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| 24 |
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https://doi.org/10.1108/EL-08-2024-0253
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| 25 |
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Companion code: https://github.com/sasa5linkar/Serbian-WordNet-Sentiment-Lexicon-Analysis
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| 26 |
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License documentation change, 23 September 2026:
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The existing `apache-2.0` declaration was retained and expanded with the full license text and attribution on 23 September 2026.
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| 29 |
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Model weights, configuration, and tokenizer files were not modified.
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| 30 |
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| 31 |
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External data and code keep their own terms. The exact SrpWN training-release
|
| 32 |
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permissions remain to be documented; see README.md, License / Scope and
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training-resource permissions. This notice provides attribution and provenance;
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it does not add conditions to the license. Warranty and liability provisions
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are set out in LICENSE.
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README.md
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## License
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## Citation
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## License
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This fine-tuned model is distributed under **Apache License 2.0** (`apache-2.0`), matching the license declared for its original base model, [classla/bcms-bertic](https://huggingface.co/classla/bcms-bertic/blob/5db9755d6152ec6403c0201223e4848bd1b98a48/README.md). Read the full [LICENSE](LICENSE) and [NOTICE](NOTICE) for attribution and the description of the fine-tuning changes.
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The license permits use, modification, and distribution, including commercial use, subject to its terms. When redistributing, include the license, retain applicable attribution and notices, and mark modifications. It does not require every derivative work to use the same license.
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### Scope and training-resource permissions
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The model license covers the model distribution and accompanying documentation within the rights the licensors can grant. External lexical resources, training datasets, and companion code retain their own terms.
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An earlier description of Serbian WordNet reports **CC BY-NC** terms for the downloadable resource ([Developing and Maintaining a WordNet: Procedures and Tools, 2014](https://aclanthology.org/W14-0108.pdf)). The terms of the exact SrpWN release used for this fine-tuning, and any separate permission covering it, have not been verified in this documentation update. That historical statement alone does not determine the license of the trained weights. This model-license declaration does not grant rights to redistribute SrpWN or establish that every third-party permission for a particular use has been cleared. The remaining check is to identify the training release and record the applicable permission from its rights holders. See also [Creative Commons guidance on AI training](https://creativecommons.org/faq/#artificial-intelligence-and-cc-licenses).
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### License declaration history
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The existing `apache-2.0` declaration was retained and expanded with the full license text and attribution on 23 September 2026.
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## Citation
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