Instructions to use floflodebilbao/LoRA_LED_all_aspects with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use floflodebilbao/LoRA_LED_all_aspects with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("allenai/led-base-16384") model = PeftModel.from_pretrained(base_model, "floflodebilbao/LoRA_LED_all_aspects") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from floflodebilbao/LoRA_LED_all_aspects: direct link, hf CLI and curl.
- Browser
- Download file 5.91 kB
-
https://huggingface.co/floflodebilbao/LoRA_LED_all_aspects/resolve/main/training_args.bin
- Command line
-
hf download hf://floflodebilbao/LoRA_LED_all_aspects/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/floflodebilbao/LoRA_LED_all_aspects/resolve/main/training_args.bin
5.91 kB
- Xet hash:
- edc765933ed065a2ac682233f51f0c0ed68fa5353fc651be590d34a765f9ddd1
- Size of remote file:
- 5.91 kB
- SHA256:
- 34933176b8040dc6b117745691aa0f33d8cb6d10d0f117b36a8461f5f49eac76
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