Instructions to use Linhz/Vinewsqa_bartpho_qag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Linhz/Vinewsqa_bartpho_qag with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Linhz/Vinewsqa_bartpho_qag") model = AutoModelForSeq2SeqLM.from_pretrained("Linhz/Vinewsqa_bartpho_qag", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Linhz/Vinewsqa_bartpho_qag: direct link, hf CLI and curl.
- Browser
- Download file 527 MB
-
https://huggingface.co/Linhz/Vinewsqa_bartpho_qag/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Linhz/Vinewsqa_bartpho_qag/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Linhz/Vinewsqa_bartpho_qag/resolve/main/pytorch_model.bin
527 MB
- Xet hash:
- 83750c427c4d6b33b1ec6d14ed93b1baacf51cecb09a7f0be2503b5d14fd7fa6
- Size of remote file:
- 527 MB
- SHA256:
- 03672a983a8313f58cde976b200b0b7893b2a12ada9cad3ab690538f38d10653
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