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:
- f4397172d59e3d7a94dde6b74618523ca8c399957083a9730709cdd341ff19c3
- Size of remote file:
- 8.55 kB
- SHA256:
- e32a599a82e666c0458e09c52d6a1178a2eb11619e1d17bfd52e722a62f9d831
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.