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 pytorch_model.bin from laamaai/bart-large-neutralization: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/laamaai/bart-large-neutralization/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://laamaai/bart-large-neutralization/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/laamaai/bart-large-neutralization/resolve/main/pytorch_model.bin
1.63 GB
- Xet hash:
- 61649bbb2b8a67df0840388405b501c95e20df74973365389eb2b860b59ad130
- Size of remote file:
- 1.63 GB
- SHA256:
- c5baa3361f5f583a708f5eead53fca0fab22df759f2864a5364658c475268097
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