Translation
Transformers
PyTorch
Polish
t5
text2text-generation
T5
summarization
question answering
reading comprehension
text-generation-inference
Instructions to use allegro/plt5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allegro/plt5-base 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="allegro/plt5-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("allegro/plt5-base") model = AutoModelForSeq2SeqLM.from_pretrained("allegro/plt5-base") - Notebooks
- Google Colab
- Kaggle
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README.md
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license: cc-by-4.0
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---
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# plT5
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**plT5** models are T5-based language models trained on Polish corpora. Models were optimized for the original T5 denoising target.
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## Corpus
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```python
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("allegro/plT5-
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model = AutoModel.from_pretrained("allegro/plT5-
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```
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## License
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license: cc-by-4.0
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---
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# plT5 Base
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**plT5** models are T5-based language models trained on Polish corpora. Models were optimized for the original T5 denoising target.
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## Corpus
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```python
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("allegro/plT5-base")
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model = AutoModel.from_pretrained("allegro/plT5-base")
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```
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## License
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