Instructions to use scott156/LED-Base-NSPCC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scott156/LED-Base-NSPCC with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("scott156/LED-Base-NSPCC") model = AutoModelForSeq2SeqLM.from_pretrained("scott156/LED-Base-NSPCC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from scott156/LED-Base-NSPCC: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/scott156/LED-Base-NSPCC/resolve/main/training_args.bin
- Command line
-
hf download hf://scott156/LED-Base-NSPCC/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/scott156/LED-Base-NSPCC/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 51e36353d59e40894333867f2c8b0e76bfa19fa5ac29de34c6180365ac3d2ad9
- Size of remote file:
- 5.11 kB
- SHA256:
- 4dcfb8858f633afebddde211045997d8c8b50d596a47d15722c8713b046731da
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