Instructions to use SZTAKI-HLT/mT5-base-HunSum-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SZTAKI-HLT/mT5-base-HunSum-1 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="SZTAKI-HLT/mT5-base-HunSum-1")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SZTAKI-HLT/mT5-base-HunSum-1") model = AutoModelForSeq2SeqLM.from_pretrained("SZTAKI-HLT/mT5-base-HunSum-1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd73ab64bc7fbbfe8c8c3b69d389def77232066ce94bbb3f8859d0ea9fca8f47
- Size of remote file:
- 2.33 GB
- SHA256:
- 12f9b86e698cde325dc1d2b6f8f09f0f127f792a20f3e4a3c968437b31f55891
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