Instructions to use ar5entum/bart_rom_dev_tl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ar5entum/bart_rom_dev_tl with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ar5entum/bart_rom_dev_tl") model = AutoModelForSeq2SeqLM.from_pretrained("ar5entum/bart_rom_dev_tl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ar5entum/bart_rom_dev_tl: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/ar5entum/bart_rom_dev_tl/resolve/main/training_args.bin
- Command line
-
hf download hf://ar5entum/bart_rom_dev_tl/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ar5entum/bart_rom_dev_tl/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 6d0c104f065d989fea06f6f02d3234e4f5734fc984d0353f1a17b25865c5a8bd
- Size of remote file:
- 5.37 kB
- SHA256:
- b0fb23e2da51837acf9ee0931db6be86c1ae67d61c417fcd253d2fd6dec1835e
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