Instructions to use Ayham/distilbert_gpt2_summarization_xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ayham/distilbert_gpt2_summarization_xsum with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Ayham/distilbert_gpt2_summarization_xsum") model = AutoModelForSeq2SeqLM.from_pretrained("Ayham/distilbert_gpt2_summarization_xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1ccb9269c2bbeff3cbf76f4516a678e60aff6da26d5a9af43a6c3104ed5f1e7
- Size of remote file:
- 897 MB
- SHA256:
- bb4b03370a907c13d892855d264b84f656dc1c3bd1db4ac4c4f3e6d753137607
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