Instructions to use HatimF/bartL_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HatimF/bartL_3 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("HatimF/bartL_3") model = AutoModelForSeq2SeqLM.from_pretrained("HatimF/bartL_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d83d91805a7a502c023998870553950ccfbfac3501fe0a1a6e8ee5ca4a1b8669
- Size of remote file:
- 4.79 kB
- SHA256:
- 4b7d9b58874c272b66447c777b9497de73332f708c84320ae69c0171ce0dcd0f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.