Transformers
PyTorch
mt5
text2text-generation
Summarization
abstractive summarization
mt5-base
Czech
text2text generation
text generation
Instructions to use ctu-aic/mt5-base-multilingual-summarization-multilarge-cs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ctu-aic/mt5-base-multilingual-summarization-multilarge-cs with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ctu-aic/mt5-base-multilingual-summarization-multilarge-cs") model = AutoModelForSeq2SeqLM.from_pretrained("ctu-aic/mt5-base-multilingual-summarization-multilarge-cs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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