Instructions to use floflodebilbao/LED_sum_outcome with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use floflodebilbao/LED_sum_outcome with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("floflodebilbao/LED_sum_outcome") model = AutoModelForSeq2SeqLM.from_pretrained("floflodebilbao/LED_sum_outcome", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from floflodebilbao/LED_sum_outcome: direct link, hf CLI and curl.
- Browser
- Download file 5.91 kB
-
https://huggingface.co/floflodebilbao/LED_sum_outcome/resolve/main/training_args.bin
- Command line
-
hf download hf://floflodebilbao/LED_sum_outcome/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/floflodebilbao/LED_sum_outcome/resolve/main/training_args.bin
5.91 kB
- Xet hash:
- c01ab1cf635b859ada4d358166c7bb01d03edfb5f87e3682a4e95dba67be6264
- Size of remote file:
- 5.91 kB
- SHA256:
- a793534fb04148a8677ac5b59c81ff172823a553c74cd908c3a03ed66c689403
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