Instructions to use Ayham/xlnet_gpt2_summarization_xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ayham/xlnet_gpt2_summarization_xsum with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Ayham/xlnet_gpt2_summarization_xsum") model = AutoModelForSeq2SeqLM.from_pretrained("Ayham/xlnet_gpt2_summarization_xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Ayham/xlnet_gpt2_summarization_xsum: direct link, hf CLI and curl.
- Browser
- Download file 1.1 GB
-
https://huggingface.co/Ayham/xlnet_gpt2_summarization_xsum/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Ayham/xlnet_gpt2_summarization_xsum/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Ayham/xlnet_gpt2_summarization_xsum/resolve/main/pytorch_model.bin
1.1 GB
- Xet hash:
- c12ac388fbdff8ab288b7c40fb8f5fbc3343287a61ea16fce40aa2297614292c
- Size of remote file:
- 1.1 GB
- SHA256:
- eb4ca742d624d4f24ddeca0ce71b8e7d761ca400e0cbc4a639ee9800ff08efdc
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