Instructions to use akira1608/bart-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akira1608/bart-1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("akira1608/bart-1") model = AutoModelForSeq2SeqLM.from_pretrained("akira1608/bart-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from akira1608/bart-1: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/akira1608/bart-1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://akira1608/bart-1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/akira1608/bart-1/resolve/main/pytorch_model.bin
1.63 GB
- Xet hash:
- a56f3ca76fbad07cfbda72720778b6548f6d8127df81b0960db5db062d7d8145
- Size of remote file:
- 1.63 GB
- SHA256:
- 0f9c5ca658ce498993f602d80ebdbf656d18bd0ff0d8c0afcd69e2582c6c4b92
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