Instructions to use AinhoaC/mbart-neutralization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AinhoaC/mbart-neutralization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("AinhoaC/mbart-neutralization") model = AutoModelForSeq2SeqLM.from_pretrained("AinhoaC/mbart-neutralization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AinhoaC/mbart-neutralization: direct link, hf CLI and curl.
- Browser
- Download file 2.44 GB
-
https://huggingface.co/AinhoaC/mbart-neutralization/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AinhoaC/mbart-neutralization/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AinhoaC/mbart-neutralization/resolve/main/pytorch_model.bin
2.44 GB
- Xet hash:
- 648793dc48f9fd2696db120289cb70a2e5e76e5cd1b7eab5f5a9ed6fe1c08af6
- Size of remote file:
- 2.44 GB
- SHA256:
- e5bb893a330c79801e7362d2e12c84784fd8a9032d481fcaf53e4d083f2d394f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.