Translation
Transformers
PyTorch
Safetensors
Belarusian
bart
text2text-generation
seq2seq
lemmatisation
Instructions to use djulian13/be-tiny-bart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use djulian13/be-tiny-bart 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="djulian13/be-tiny-bart")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("djulian13/be-tiny-bart") model = AutoModelForSeq2SeqLM.from_pretrained("djulian13/be-tiny-bart") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
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---
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license: mpl-2.0
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language:
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- be
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metrics:
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- accuracy
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base_model:
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pipeline_tag: translation
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tags:
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- seq2seq
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- lemmatisation
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# be-tiny-bart
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A model for lemmatisation of Belarusian, trained on [Belarusian-HSE](https://github.com/UniversalDependencies/UD_Belarusian-HSE/tree/master) dataset.
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## Model Card Contact
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ilia.afanasev.1997@gmail.com
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# be-tiny-bart
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A model for lemmatisation of Belarusian, trained on [Belarusian-HSE](https://github.com/UniversalDependencies/UD_Belarusian-HSE/tree/master) dataset.
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## Model Card Contact
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ilia.afanasev.1997@gmail.com
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---
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license: mpl-2.0
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language:
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- be
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metrics:
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- accuracy
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base_model:
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- sshleifer/bart-tiny-random
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pipeline_tag: translation
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tags:
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- seq2seq
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- lemmatisation
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---
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