Instructions to use ar5entum/bart_dev_rom_tl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ar5entum/bart_dev_rom_tl with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ar5entum/bart_dev_rom_tl") model = AutoModelForSeq2SeqLM.from_pretrained("ar5entum/bart_dev_rom_tl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ar5entum/bart_dev_rom_tl: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/ar5entum/bart_dev_rom_tl/resolve/main/training_args.bin
- Command line
-
hf download hf://ar5entum/bart_dev_rom_tl/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ar5entum/bart_dev_rom_tl/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 0778ba0c525c92874bd7e24b6105eb65d63b899b26114b237562b8dcd7b74b55
- Size of remote file:
- 5.37 kB
- SHA256:
- 5c7f00089a30b334ed1e14b4a2e40c8e94ee220605f149ae39d3548a6d59e1de
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