Instructions to use BSC-LT/salamandraTA-7b-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BSC-LT/salamandraTA-7b-instruct with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="BSC-LT/salamandraTA-7b-instruct")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("BSC-LT/salamandraTA-7b-instruct") model = AutoModelForCausalLM.from_pretrained("BSC-LT/salamandraTA-7b-instruct") - Notebooks
- Google Colab
- Kaggle
added citation
Browse files
README.md
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@@ -859,11 +859,13 @@ The Barcelona Supercomputing Center, as the owner and creator of the model, shal
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If you find our model useful, we would appreciate if you could cite our work as follows:
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}
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```
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If you find our model useful, we would appreciate if you could cite our work as follows:
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```
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@misc{gilabert2025salamandrasalamandratabscsubmission,
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title={From SALAMANDRA to SALAMANDRATA: BSC Submission for WMT25 General Machine Translation Shared Task},
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author={Javier Garcia Gilabert and Xixian Liao and Severino Da Dalt and Ella Bohman and Audrey Mash and Francesca De Luca Fornaciari and Irene Baucells and Joan Llop and Miguel Claramunt Argote and Carlos Escolano and Maite Melero},
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year={2025},
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eprint={2508.12774},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2508.12774},
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}
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```
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