Instructions to use ahotrod/electra_large_discriminator_squad2_512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahotrod/electra_large_discriminator_squad2_512 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="ahotrod/electra_large_discriminator_squad2_512")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ahotrod/electra_large_discriminator_squad2_512") model = AutoModelForQuestionAnswering.from_pretrained("ahotrod/electra_large_discriminator_squad2_512") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf0ec200e78d9ccfd7c586fb4acc012215ebaf7c527fed55a041a8496f9b2102
- Size of remote file:
- 1.34 GB
- SHA256:
- a93ff4d9e9f46938768a9f7ace495516911f27aa8681cbd30e9bc073611b3e21
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.