Instructions to use timpal0l/mdeberta-v3-base-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use timpal0l/mdeberta-v3-base-squad2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="timpal0l/mdeberta-v3-base-squad2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("timpal0l/mdeberta-v3-base-squad2") model = AutoModelForQuestionAnswering.from_pretrained("timpal0l/mdeberta-v3-base-squad2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f889c44c06246aa08fd33ae13c2a8533c2b89984812e19bf99519276a5289f7f
- Size of remote file:
- 1.11 GB
- SHA256:
- 91d05e57e35a8a3768fbdbd26ecfa3c0672f6e889c0554e1859cabf282de2c56
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