Instructions to use chitanda/merit-deberta-v2-xlarge-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chitanda/merit-deberta-v2-xlarge-v1 with Transformers:
# Load model directly from transformers import AutoTokenizer, DebertaV2ForMultipleChoicePreTrain tokenizer = AutoTokenizer.from_pretrained("chitanda/merit-deberta-v2-xlarge-v1") model = DebertaV2ForMultipleChoicePreTrain.from_pretrained("chitanda/merit-deberta-v2-xlarge-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ea8c6ee369f485d16635f72764977f55e185c1f7c06d3d4c125fe08c50065cb
- Size of remote file:
- 4.36 GB
- SHA256:
- 8e03ef6bc6f677d0f5bf42de2b766aa74524e6500629a05f2e92c98bd3da00a6
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