Instructions to use Arjav/TOS-Longformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arjav/TOS-Longformer with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Arjav/TOS-Longformer") model = AutoModelForSeq2SeqLM.from_pretrained("Arjav/TOS-Longformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Arjav/TOS-Longformer: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/Arjav/TOS-Longformer/resolve/main/training_args.bin
- Command line
-
hf download hf://Arjav/TOS-Longformer/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Arjav/TOS-Longformer/resolve/main/training_args.bin
3.9 kB
- Xet hash:
- ec3c54aea599fad8f689dc849a0fc1fa91c61309a59ff265065536c881a779de
- Size of remote file:
- 3.9 kB
- SHA256:
- 4649a3ac38c9d15b1a490305c8ec0d3808da099ef9eb3e09ced1ed6e22bdbf33
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