Instructions to use laamaai/bart-large-neutralization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use laamaai/bart-large-neutralization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("laamaai/bart-large-neutralization") model = AutoModelForSeq2SeqLM.from_pretrained("laamaai/bart-large-neutralization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from laamaai/bart-large-neutralization: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/laamaai/bart-large-neutralization/resolve/main/training_args.bin
- Command line
-
hf download hf://laamaai/bart-large-neutralization/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/laamaai/bart-large-neutralization/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- 1a2acb84e7d3ea8055cdc7456d26bd62b87b1d74ebf984318ac3e28420933084
- Size of remote file:
- 3.64 kB
- SHA256:
- d19be62fcd44b7eb9ab5ee6b07849cb3e7a40794536b166d0e591150ef95141b
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