Instructions to use jasonsurya0/BART_SIX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jasonsurya0/BART_SIX with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("jasonsurya0/BART_SIX") model = AutoModelForSeq2SeqLM.from_pretrained("jasonsurya0/BART_SIX", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jasonsurya0/BART_SIX: direct link, hf CLI and curl.
- Browser
- Download file 3.77 kB
-
https://huggingface.co/jasonsurya0/BART_SIX/resolve/main/training_args.bin
- Command line
-
hf download hf://jasonsurya0/BART_SIX/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jasonsurya0/BART_SIX/resolve/main/training_args.bin
3.77 kB
- Xet hash:
- 44723010a1b4ede89c942f081802e9f52fbb0e2c04193e3cba301dbe9d35918c
- Size of remote file:
- 3.77 kB
- SHA256:
- 542c18650b7282b0e6bc0382b8ab899b2f200733597ddf6126c6bffb1af89a1b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.