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--- |
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datasets: ctu-aic/csfever |
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--- |
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('---\ndatasets:\n- ctu-aic/csfever\nlanguages:\n- cs\nlicense: cc-by-sa-4.0\ntags:\n- natural-language-inference\n\n---',) |
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# 🦾 xlm-roberta-large-xnli-csfever |
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Transformer model for **Natural Language Inference** in ['cs'] languages finetuned on ['ctu-aic/csfever'] datasets. |
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## 🧰 Usage |
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### 👾 Using UKPLab `sentence_transformers` `CrossEncoder` |
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The model was trained using the `CrossEncoder` API and we recommend it for its usage. |
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```python |
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from sentence_transformers.cross_encoder import CrossEncoder |
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model = CrossEncoder('ctu-aic/xlm-roberta-large-xnli-csfever') |
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scores = model.predict([["My first context.", "My first hypothesis."], |
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["Second context.", "Hypothesis."]]) |
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``` |
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### 🤗 Using Huggingface `transformers` |
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```python |
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from transformers import AutoModelForSequenceClassification, AutoTokenizer |
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model = AutoModelForSequenceClassification.from_pretrained("ctu-aic/xlm-roberta-large-xnli-csfever") |
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tokenizer = AutoTokenizer.from_pretrained("ctu-aic/xlm-roberta-large-xnli-csfever") |
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``` |
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## 🌳 Contributing |
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Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. |
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## 👬 Authors |
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The model was trained and uploaded by **[ullriher](https://udb.fel.cvut.cz/?uid=ullriher&sn=&givenname=&_cmd=Hledat&_reqn=1&_type=user&setlang=en)** (e-mail: [ullriher@fel.cvut.cz](mailto:ullriher@fel.cvut.cz)) |
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The code was codeveloped by the NLP team at Artificial Intelligence Center of CTU in Prague ([AIC](https://www.aic.fel.cvut.cz/)). |
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## 🔐 License |
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[cc-by-sa-4.0](https://choosealicense.com/licenses/cc-by-sa-4.0) |
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## 💬 Citation |
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If you find this repository helpful, feel free to cite our publication: |
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``` |
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@article{DBLP:journals/corr/abs-2201-11115, |
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author = {Herbert Ullrich and |
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Jan Drchal and |
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Martin R{'{y}}par and |
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Hana Vincourov{'{a}} and |
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V{'{a}}clav Moravec}, |
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title = {CsFEVER and CTKFacts: Acquiring Czech Data for Fact Verification}, |
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journal = {CoRR}, |
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volume = {abs/2201.11115}, |
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year = {2022}, |
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url = {https://arxiv.org/abs/2201.11115}, |
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eprinttype = {arXiv}, |
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eprint = {2201.11115}, |
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timestamp = {Tue, 01 Feb 2022 14:59:01 +0100}, |
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biburl = {https://dblp.org/rec/journals/corr/abs-2201-11115.bib}, |
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bibsource = {dblp computer science bibliography, https://dblp.org} |
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} |
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``` |
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