Instructions to use csebuetnlp/mT5_multilingual_XLSum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use csebuetnlp/mT5_multilingual_XLSum 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_multilingual_XLSum")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("csebuetnlp/mT5_multilingual_XLSum") model = AutoModelForSeq2SeqLM.from_pretrained("csebuetnlp/mT5_multilingual_XLSum") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28677e666c17134b1ae5c9561a011f0b04d0d35d7908cb8414e10fdbda2ac7b5
- Size of remote file:
- 2.33 GB
- SHA256:
- 1899a041aceedfd0c9c67e87f2597bc597ce6f4c1f21b5d35a6325322608a898
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