Instructions to use Ayham/bert_gpt2_summarization_xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ayham/bert_gpt2_summarization_xsum with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Ayham/bert_gpt2_summarization_xsum") model = AutoModelForSeq2SeqLM.from_pretrained("Ayham/bert_gpt2_summarization_xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e51ba9b192d756ab1dbe7c935ccdfd28ebcf20fbdf2c9329f674de23d1a0679
- Size of remote file:
- 2.99 kB
- SHA256:
- fd87a18b5a07325e1d9788c7d464a776bb3ef71e4cb4a577fb32a60b8a353b11
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