Instructions to use voidful/bart_base_squad_cq_a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/bart_base_squad_cq_a with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("voidful/bart_base_squad_cq_a") model = AutoModelForSeq2SeqLM.from_pretrained("voidful/bart_base_squad_cq_a", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f9f5522009a3d6b0e05c6bf48323df75435b9387778a9b62aa5a1158dc720f8
- Size of remote file:
- 712 MB
- SHA256:
- 0d28184fc433d33d4c99263ce3c26fa6389328d11c461ddb5c2bef777b61f684
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.