Instructions to use uzaaft/bart_lfqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uzaaft/bart_lfqa with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("uzaaft/bart_lfqa") model = AutoModelForSeq2SeqLM.from_pretrained("uzaaft/bart_lfqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61c94410d33bcbbf45f534e7bd0807fdb542591950989610ec4e5654b2b151e3
- Size of remote file:
- 916 MB
- SHA256:
- 54856402faf7472d14e52302edf9889ec4c0b0c08902a1335da6337f9085ead9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.