Transformers
PyTorch
Czech
Czech
mbart
text2text-generation
abstractive summarization
mbart-cc25
Czech
Instructions to use krotima1/mbart-at2h-s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use krotima1/mbart-at2h-s with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("krotima1/mbart-at2h-s") model = AutoModelForSeq2SeqLM.from_pretrained("krotima1/mbart-at2h-s") - Notebooks
- Google Colab
- Kaggle
| {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "src_lang": "cs_CZ", "tgt_lang": "cs_CZ", "additional_special_tokens": null, "model_max_length": 1024, "special_tokens_map_file": null, "name_or_path": "facebook/mbart-large-cc25", "tokenizer_class": "MBartTokenizer"} |