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:
- 74c73e587b34f48998e32329452cf051498e0489781e49a7cd9331ae4da33e85
- Size of remote file:
- 2.99 kB
- SHA256:
- 58507ce38218a728904ad8edef8813e13407cde9a15b4e05e4993b1e855e634f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.