Transformers
PyTorch
mbart
text2text-generation
Summarization
abstractive summarization
mbart-large-cc25
Czech
text2text generation
text generation
Instructions to use ctu-aic/mbart25-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/mbart25-multilingual-summarization-multilarge-cs with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ctu-aic/mbart25-multilingual-summarization-multilarge-cs") model = AutoModelForSeq2SeqLM.from_pretrained("ctu-aic/mbart25-multilingual-summarization-multilarge-cs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ctu-aic/mbart25-multilingual-summarization-multilarge-cs: direct link, hf CLI and curl.
- Browser
- Download file 2.44 GB
-
https://huggingface.co/ctu-aic/mbart25-multilingual-summarization-multilarge-cs/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://ctu-aic/mbart25-multilingual-summarization-multilarge-cs@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ctu-aic/mbart25-multilingual-summarization-multilarge-cs/resolve/refs%2Fpr%2F2/pytorch_model.bin
2.44 GB
- Xet hash:
- 6d694acb68503c8d7b6937737719d8ef47d7aea62e4f832584f1b12b59612665
- Size of remote file:
- 2.44 GB
- SHA256:
- f58a7275e3d3fb222fdbcaaccb8650f94ee334bc8347b186d843450e65f39641
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