Instructions to use akira1608/BART-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akira1608/BART-model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("akira1608/BART-model") model = AutoModelForSeq2SeqLM.from_pretrained("akira1608/BART-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from akira1608/BART-model: direct link, hf CLI and curl.
- Browser
- Download file 2.28 GB
-
https://huggingface.co/akira1608/BART-model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://akira1608/BART-model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/akira1608/BART-model/resolve/main/pytorch_model.bin
2.28 GB
- Xet hash:
- 6208e5884dea8abef6005e658c39904cc1aaa12b3623a559712d2b0f0ebf70b3
- Size of remote file:
- 2.28 GB
- SHA256:
- 357b53cdec2b8c6835920c96f07ace66112839e52ee20f546130f2014d579dcd
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