Instructions to use shahadalll/mt5-base-finetuned-mt5-summarization-task with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shahadalll/mt5-base-finetuned-mt5-summarization-task with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("shahadalll/mt5-base-finetuned-mt5-summarization-task") model = AutoModelForMultimodalLM.from_pretrained("shahadalll/mt5-base-finetuned-mt5-summarization-task") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 635242e9f1988327923aa7e804b4ca95889b07087d6b3b5b8c44926a091a918e
- Size of remote file:
- 4.92 kB
- SHA256:
- b248bb46ddba869b5b54e5d6b3c5dfdf1b55147bb0cf76500ab24d46fa9b71c6
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