Instructions to use MingZhong/unieval-sum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MingZhong/unieval-sum with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("MingZhong/unieval-sum") model = AutoModelForSeq2SeqLM.from_pretrained("MingZhong/unieval-sum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8a161530bb53670e3a09a188c3788c00480eb8733be24d8780f2c307b72d6b8
- Size of remote file:
- 3.13 GB
- SHA256:
- 5965efa9fb9ba88b0b7dc4e074e247119ee62e1e105ea314d2af50c91b32354f
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