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:
- 0d20616c32c41f34c07387feea28f5a911ad7e505611b5890246fce00aef50d4
- Size of remote file:
- 1.07 GB
- SHA256:
- 9fffe470677cb5321261df6a0175d737be4bf2b42e9952c18e66497f553a077e
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