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:
# pip install -U transformers accelerate # 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
Download pytorch_model.bin from Ayham/distilbert_gpt2_summarization_xsum: direct link, hf CLI and curl.
- Browser
- Download file 897 MB
-
https://huggingface.co/Ayham/distilbert_gpt2_summarization_xsum/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Ayham/distilbert_gpt2_summarization_xsum/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Ayham/distilbert_gpt2_summarization_xsum/resolve/main/pytorch_model.bin
897 MB
- Xet hash:
- f1ccb9269c2bbeff3cbf76f4516a678e60aff6da26d5a9af43a6c3104ed5f1e7
- Size of remote file:
- 897 MB
- SHA256:
- bb4b03370a907c13d892855d264b84f656dc1c3bd1db4ac4c4f3e6d753137607
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