Instructions to use SZTAKI-HLT/mT5-base-HunSum-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SZTAKI-HLT/mT5-base-HunSum-2 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-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SZTAKI-HLT/mT5-base-HunSum-2") model = AutoModelForSeq2SeqLM.from_pretrained("SZTAKI-HLT/mT5-base-HunSum-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f03cb145a990ed2c1223e4b4a46c5327bc1c07cafea529a2649da90fd8d00c97
- Size of remote file:
- 2.33 GB
- SHA256:
- e6afbc5cb61efd920f56bfa309c135f59cf19509667347b600b1a7ee113fb685
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