Instructions to use floflodebilbao/LEDv3_ACLsum_all_aspects with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use floflodebilbao/LEDv3_ACLsum_all_aspects with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("floflodebilbao/LEDv3_ACLsum_all_aspects") model = AutoModelForSeq2SeqLM.from_pretrained("floflodebilbao/LEDv3_ACLsum_all_aspects", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from floflodebilbao/LEDv3_ACLsum_all_aspects: direct link, hf CLI and curl.
- Browser
- Download file 5.91 kB
-
https://huggingface.co/floflodebilbao/LEDv3_ACLsum_all_aspects/resolve/main/training_args.bin
- Command line
-
hf download hf://floflodebilbao/LEDv3_ACLsum_all_aspects/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/floflodebilbao/LEDv3_ACLsum_all_aspects/resolve/main/training_args.bin
5.91 kB
- Xet hash:
- eb8b208f005fa4127652ed5ac260b8433e4aa93d661ae0058eeb7c617a22af50
- Size of remote file:
- 5.91 kB
- SHA256:
- 48089e91074ad3d1b0252b19ff9a4475c377591e49ea8005c801bea3b4bc7040
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