Instructions to use ashleychen/bart-finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashleychen/bart-finetuning with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ashleychen/bart-finetuning") model = AutoModelForSeq2SeqLM.from_pretrained("ashleychen/bart-finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ashleychen/bart-finetuning: direct link, hf CLI and curl.
- Browser
- Download file 3.5 kB
-
https://huggingface.co/ashleychen/bart-finetuning/resolve/main/training_args.bin
- Command line
-
hf download hf://ashleychen/bart-finetuning/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ashleychen/bart-finetuning/resolve/main/training_args.bin
3.5 kB
- Xet hash:
- 72c4fdfa9fb109c54458593664decef78bdfc462097a9a29f026f04d07fe601c
- Size of remote file:
- 3.5 kB
- SHA256:
- 826e2107b439d908712876de5b0c01d4d63f9a321c00aa7f4f40ce070bdec3a9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.