Instructions to use voidful/changpt-bart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/changpt-bart with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("voidful/changpt-bart") model = AutoModelForSeq2SeqLM.from_pretrained("voidful/changpt-bart", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from voidful/changpt-bart: direct link, hf CLI and curl.
- Browser
- Download file 719 MB
-
https://huggingface.co/voidful/changpt-bart/resolve/f7a4e21baa0d896bc3b7c21f8e7cbb77e5b353b7/pytorch_model.bin
- Command line
-
hf download hf://voidful/changpt-bart@f7a4e21baa0d896bc3b7c21f8e7cbb77e5b353b7/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/voidful/changpt-bart/resolve/f7a4e21baa0d896bc3b7c21f8e7cbb77e5b353b7/pytorch_model.bin
719 MB
- Xet hash:
- 34a880d12d5e2fe8fada9245465a28621fb9c22d8040ff4d0635a5b5a6fdb763
- Size of remote file:
- 719 MB
- SHA256:
- cc24a47579e9b2cb5a8eb42321b8510f7ac5e71cf0b82c9a27accda086c2dc6b
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