Instructions to use Dundalia/BART_lfqa_oracle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dundalia/BART_lfqa_oracle with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Dundalia/BART_lfqa_oracle") model = AutoModelForSeq2SeqLM.from_pretrained("Dundalia/BART_lfqa_oracle", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c76c8cbac5f39c216d470d08d0eee596d2dd5399d1971d90bbae2173a579c00
- Size of remote file:
- 1.63 GB
- SHA256:
- 6b9dee5500cf7340ec020ba435244e47b1d417399c74bf3d04b43513901bdbfb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.