Instructions to use LiqiangXiao/summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LiqiangXiao/summarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("LiqiangXiao/summarization") model = AutoModelForSeq2SeqLM.from_pretrained("LiqiangXiao/summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from LiqiangXiao/summarization: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/LiqiangXiao/summarization/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://LiqiangXiao/summarization/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/LiqiangXiao/summarization/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- 3fde4f030cc6c262eff132a0926a42dd32f03e14e0a7c9fdf5700765b663e560
- Size of remote file:
- 558 MB
- SHA256:
- b0da0c5c2088e0e1de73f86a56c08e1318abcdec60ed8b94c8f62e95adf7e6fa
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