Instructions to use floflodebilbao/Lora_LED_sum_approach with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use floflodebilbao/Lora_LED_sum_approach 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_sum_approach") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from floflodebilbao/Lora_LED_sum_approach: direct link, hf CLI and curl.
- Browser
- Download file 5.91 kB
-
https://huggingface.co/floflodebilbao/Lora_LED_sum_approach/resolve/main/training_args.bin
- Command line
-
hf download hf://floflodebilbao/Lora_LED_sum_approach/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/floflodebilbao/Lora_LED_sum_approach/resolve/main/training_args.bin
5.91 kB
- Xet hash:
- ed1b9ff9d664e71a14043a12267515a9e301a00c5aa6d1d0028ef66a12d17362
- Size of remote file:
- 5.91 kB
- SHA256:
- 810d98a4ae868b7d5808dd9692ee181fbeb401f160ea197254fca7c032c54b19
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