Instructions to use Koltunov-Matthew/my_mdeberta_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Koltunov-Matthew/my_mdeberta_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Koltunov-Matthew/my_mdeberta_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Koltunov-Matthew/my_mdeberta_model") model = AutoModelForQuestionAnswering.from_pretrained("Koltunov-Matthew/my_mdeberta_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9b44aa0805d0cb8345b6effa32bd35825a52643f8a20acbb5f8a7c0380985b7
- Size of remote file:
- 16.3 MB
- SHA256:
- 77c3df135e6f934ea382c695552f34550481be029af7808a3d82f4a5792e01bf
路
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