Instructions to use allenai/led-base-16384-multi_lexsum-source-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allenai/led-base-16384-multi_lexsum-source-tiny with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("allenai/led-base-16384-multi_lexsum-source-tiny") model = AutoModelForSeq2SeqLM.from_pretrained("allenai/led-base-16384-multi_lexsum-source-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from allenai/led-base-16384-multi_lexsum-source-tiny: direct link, hf CLI and curl.
- Browser
- Download file 648 MB
-
https://huggingface.co/allenai/led-base-16384-multi_lexsum-source-tiny/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://allenai/led-base-16384-multi_lexsum-source-tiny/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/allenai/led-base-16384-multi_lexsum-source-tiny/resolve/main/pytorch_model.bin
648 MB
- Xet hash:
- b1ca3d703a667d791c210fb1d77fe5cd62cecf4d5e004e61757c5afea95745ee
- Size of remote file:
- 648 MB
- SHA256:
- a0c867434ab1dd00494a2d7c8aa903fa3411011224689592af52a2895e226e75
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