Instructions to use patrickvonplaten/led-large-16384-pubmed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use patrickvonplaten/led-large-16384-pubmed with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("patrickvonplaten/led-large-16384-pubmed") model = AutoModelForSeq2SeqLM.from_pretrained("patrickvonplaten/led-large-16384-pubmed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from patrickvonplaten/led-large-16384-pubmed: direct link, hf CLI and curl.
- Browser
- Download file 1.84 GB
-
https://huggingface.co/patrickvonplaten/led-large-16384-pubmed/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://patrickvonplaten/led-large-16384-pubmed/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/patrickvonplaten/led-large-16384-pubmed/resolve/main/pytorch_model.bin
1.84 GB
- Xet hash:
- 22b787e9e216bd8eb54302f5004e4b923843861232da066b3d4758fd69d9e602
- Size of remote file:
- 1.84 GB
- SHA256:
- ef47f24d7237e4feaf49a6c9f3336cd6ade470fa28a4c5d063c4c073cde0ba77
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