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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
TemporalMesh Transformer: 29.4 PPL at 48% compute — beats Mamba, new open-source architecture
#2 opened 2 months ago
by
vigneshwar234
Adding `safetensors` variant of this model
#1 opened over 3 years ago
by
SFconvertbot