Instructions to use floflodebilbao/Lora_LED_sum_challenge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use floflodebilbao/Lora_LED_sum_challenge 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_challenge") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from floflodebilbao/Lora_LED_sum_challenge: direct link, hf CLI and curl.
- Browser
- Download file 5.91 kB
-
https://huggingface.co/floflodebilbao/Lora_LED_sum_challenge/resolve/main/training_args.bin
- Command line
-
hf download hf://floflodebilbao/Lora_LED_sum_challenge/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/floflodebilbao/Lora_LED_sum_challenge/resolve/main/training_args.bin
5.91 kB
- Xet hash:
- 7d55a94c20e04bce9aa1010d6da1a9499d9da5fdee4dae7e4e5016e3ed8ddc35
- Size of remote file:
- 5.91 kB
- SHA256:
- f9a7bcb03026319cb27e62b6a941aa99fbfe4af3a1e2071641995ca5d6ea421d
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