Instructions to use allenai/led-base-16384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allenai/led-base-16384 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("allenai/led-base-16384") model = AutoModelForSeq2SeqLM.from_pretrained("allenai/led-base-16384", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from allenai/led-base-16384: direct link, hf CLI and curl.
- Browser
- Download file 648 MB
-
https://huggingface.co/allenai/led-base-16384/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://allenai/led-base-16384/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/allenai/led-base-16384/resolve/main/pytorch_model.bin
648 MB
- Xet hash:
- 22ade2a8fe05c231a4816d9d1232834c39b54ea6938612fc5935e9d82bf06853
- Size of remote file:
- 648 MB
- SHA256:
- 779cd73728a82f1dbecbbc93d07c737c3f036d782c19bdf953479004e7dbd6d3
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