Instructions to use skoneru/iwslt_ape_ende with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use skoneru/iwslt_ape_ende with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("skoneru/iwslt_ape_ende", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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- de
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base_model:
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- Unbabel/TowerInstruct-13B-v0.1
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---
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# KIT IWSLT25 Automatic Post-Editing Model
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output = model.generate(**inputs, num_beams=num_beams, max_new_tokens=256, return_dict_in_generate=True, early_stopping=True, do_sample=False)
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hyps = tokenizer.batch_decode(output.sequences[:,inputs.input_ids.shape[1]:], skip_special_tokens=True)
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print(hyps)
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```
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- de
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base_model:
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- Unbabel/TowerInstruct-13B-v0.1
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tags:
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- Automatic Post Editing
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- Machine Translation
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model-index:
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- name: iwslt_ape_ende
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results: []
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paper:
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title: "KIT's Offline Speech Translation and Instruction Following Submission for IWSLT 2025"
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authors: "Koneru, Sai and Z{\"u}fle, Maike and Nguyen, Thai-Binh and Akti, Seymanur and Niehues, Jan and Waibel, Alexander"
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url: https://arxiv.org/abs/2505.13036
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published: 2025-05-25
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---
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# KIT IWSLT25 Automatic Post-Editing Model
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output = model.generate(**inputs, num_beams=num_beams, max_new_tokens=256, return_dict_in_generate=True, early_stopping=True, do_sample=False)
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hyps = tokenizer.batch_decode(output.sequences[:,inputs.input_ids.shape[1]:], skip_special_tokens=True)
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print(hyps)
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```
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## 📖 Citation
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If you use this model in your research, please cite:
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```bibtex
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@inproceedings{koneru2025kit,
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title={KIT's Offline Speech Translation and Instruction Following Submission for IWSLT 2025},
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author={Koneru, Sai and Z{\"u}fle, Maike and Nguyen, Thai-Binh and Akti, Seymanur and Niehues, Jan and Waibel, Alexander},
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journal={arXiv preprint arXiv:2505.13036},
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year={2025},
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url={https://arxiv.org/abs/2505.13036}
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}
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