Transformers
PyTorch
m2m_100
text2text-generation
Summarization
abstractive summarization
multilingual summarization
m2m100_418M
Czech
text2text generation
text generation
Instructions to use ctu-aic/m2m100-418M-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/m2m100-418M-multilingual-summarization-multilarge-cs with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ctu-aic/m2m100-418M-multilingual-summarization-multilarge-cs") model = AutoModelForSeq2SeqLM.from_pretrained("ctu-aic/m2m100-418M-multilingual-summarization-multilarge-cs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03c5c468fac85bafa3d3639303dfd3848bbe8b87d5cc78b36e22630e2c6591ae
- Size of remote file:
- 1.94 GB
- SHA256:
- 115734a58648fa70bf2634e939fbf25ebeb00d356c80351252f5760c22c0171a
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