Instructions to use FuuToru/MRC-processed-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FuuToru/MRC-processed-squad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="FuuToru/MRC-processed-squad")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("FuuToru/MRC-processed-squad") model = AutoModelForQuestionAnswering.from_pretrained("FuuToru/MRC-processed-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 901f64ccbfa19ff6bb5682a13e71feeb9df28cf0ea51111dc60333fc5b1ce96e
- Size of remote file:
- 2.24 GB
- SHA256:
- 7e5d6c0778c3866410d4efdb40338353664fbfc6588c3d3fa8d77f93e9046fb8
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.