Instructions to use VMware/tinyroberta-quantized-mrqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VMware/tinyroberta-quantized-mrqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="VMware/tinyroberta-quantized-mrqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("VMware/tinyroberta-quantized-mrqa") model = AutoModelForQuestionAnswering.from_pretrained("VMware/tinyroberta-quantized-mrqa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6976caf509d9a92715318551e78fad8ec2a2e4879995a87de3c175c12fbf4e3d
- Size of remote file:
- 199 MB
- SHA256:
- d55766d95ba0c46c1d7fb37d28459d57cbf44179e279d6aaa5884c5237eeb3f8
路
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