Instructions to use floflodebilbao/LED_sum_challenge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use floflodebilbao/LED_sum_challenge with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("floflodebilbao/LED_sum_challenge") model = AutoModelForSeq2SeqLM.from_pretrained("floflodebilbao/LED_sum_challenge", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from floflodebilbao/LED_sum_challenge: direct link, hf CLI and curl.
- Browser
- Download file 3.56 MB
-
https://huggingface.co/floflodebilbao/LED_sum_challenge/resolve/main/tokenizer.json
- Command line
-
hf download hf://floflodebilbao/LED_sum_challenge/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/floflodebilbao/LED_sum_challenge/resolve/main/tokenizer.json
3.56 MB
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