Instructions to use Ayham/xlnet_gpt_xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ayham/xlnet_gpt_xsum with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Ayham/xlnet_gpt_xsum") model = AutoModelForSeq2SeqLM.from_pretrained("Ayham/xlnet_gpt_xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Ayham/xlnet_gpt_xsum: direct link, hf CLI and curl.
- Browser
- Download file 1.1 GB
-
https://huggingface.co/Ayham/xlnet_gpt_xsum/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Ayham/xlnet_gpt_xsum/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Ayham/xlnet_gpt_xsum/resolve/main/pytorch_model.bin
1.1 GB
- Xet hash:
- 421d5ec19517405ef76636df9e8ecf3ab26459766c12185d7451f2f328ac1fb2
- Size of remote file:
- 1.1 GB
- SHA256:
- cbd8d55000a5e6c2b709c7ad4b3fc4dc572dd84b634c67565da00a012828592e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.