Instructions to use AnonymousSub/SQuAD_CLIP_text_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousSub/SQuAD_CLIP_text_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="AnonymousSub/SQuAD_CLIP_text_1")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("AnonymousSub/SQuAD_CLIP_text_1") model = AutoModelForQuestionAnswering.from_pretrained("AnonymousSub/SQuAD_CLIP_text_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ac18571ad1ec43e1c27c4c67e87e1b083b8feb2c544c6c740fbbc53b9c5500f
- Size of remote file:
- 496 MB
- SHA256:
- 4f7093e301df944b7f90d657091c269fa8d6e766d981804bf0ae8dc5df8dca66
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.