Transformers
PyTorch
t5
text2text-generation
summarization_2
Generated from Trainer
text-generation-inference
Instructions to use Natet/rut5_base_sum_gazeta-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Natet/rut5_base_sum_gazeta-finetuned with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Natet/rut5_base_sum_gazeta-finetuned") model = AutoModelForSeq2SeqLM.from_pretrained("Natet/rut5_base_sum_gazeta-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "additional_special_tokens": null, | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "</s>", | |
| "extra_ids": 0, | |
| "max_length": 200, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "<pad>", | |
| "pad_token_type_id": 0, | |
| "padding_side": "right", | |
| "sp_model_kwargs": {}, | |
| "stride": 0, | |
| "tokenizer_class": "T5Tokenizer", | |
| "truncation_side": "right", | |
| "truncation_strategy": "longest_first", | |
| "unk_token": "<unk>" | |
| } | |