Instructions to use qBob/BART_corrector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use qBob/BART_corrector with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("qBob/BART_corrector") model = AutoModelForSeq2SeqLM.from_pretrained("qBob/BART_corrector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
This is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.29f2212
-
Update README.md
acb3907 -
Update README.md
7ef73ee -
Update README.md
fd44bfb -
Update README.md
f890db0 -
Update README.md
6ae8027
-
update model card README.md
da35e56 -
End of training
69415cb -
Training in progress, step 500
b3de50a
-
update model card README.md
38e1d29 -
End of training
7fa90a5 -
Training in progress, step 500
e634c07 -
initial commit
6c4a851