Translation
Transformers
PyTorch
Polish
t5
text2text-generation
T5
summarization
question answering
reading comprehension
text-generation-inference
Instructions to use allegro/plt5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allegro/plt5-small 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-small")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("allegro/plt5-small") model = AutoModelForSeq2SeqLM.from_pretrained("allegro/plt5-small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84a9884b64c84d61721be76ef44c77d189dcf96f70896236473a3370d8abeeee
- Size of remote file:
- 381 MB
- SHA256:
- 070b30b393f608cc296e0ac3d0d56532282fb45bd8af00843a8ad11c91b588b7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.