Instructions to use csebuetnlp/mT5_m2o_chinese_simplified_crossSum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use csebuetnlp/mT5_m2o_chinese_simplified_crossSum with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="csebuetnlp/mT5_m2o_chinese_simplified_crossSum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("csebuetnlp/mT5_m2o_chinese_simplified_crossSum") model = AutoModelForSeq2SeqLM.from_pretrained("csebuetnlp/mT5_m2o_chinese_simplified_crossSum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>", "additional_special_tokens": ["β<extra_id_64>", "β<extra_id_95>", "β<extra_id_92>", "β<extra_id_57>", "β<extra_id_66>", "β<extra_id_59>", "β<extra_id_55>", "β<extra_id_69>", "β<extra_id_89>", "β<extra_id_72>", "β<extra_id_56>", "β<extra_id_78>", "β<extra_id_90>", "β<extra_id_98>", "β<extra_id_62>", "β<extra_id_99>", "β<extra_id_70>", "β<extra_id_94>", "β<extra_id_86>", "β<extra_id_79>", "β<extra_id_58>", "β<extra_id_65>", "β<extra_id_76>", "β<extra_id_85>", "β<extra_id_60>", "β<extra_id_82>", "β<extra_id_63>", "β<extra_id_75>", "β<extra_id_71>", "β<extra_id_88>", "β<extra_id_68>", "β<extra_id_80>", "β<extra_id_96>", "β<extra_id_81>", "β<extra_id_67>", "β<extra_id_77>", "β<extra_id_93>", "β<extra_id_83>", "β<extra_id_84>", "β<extra_id_97>", "β<extra_id_61>", "β<extra_id_91>", "β<extra_id_87>", "β<extra_id_73>", "β<extra_id_74>"]} |