Comments (4)
cdpierse
commented on May 21, 2024
Hi @subhamkhemka if you are looking to see if the explainer is utilizing the gpu you can check that via zero_shot_explainer.device this should dictate whether the device in use is GPU or CPU. Thanks.
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subhamkhemka
commented on May 21, 2024
zero_shot_explainer.device
device(type='cpu')
How do I make it use gpu ?
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cdpierse
commented on May 21, 2024
Hi @subhamkhemka to make sure that your model is on GPU assuming your machine has a compatible GPU available I believe you can call model.cuda() or model.to("cuda") to move the model onto the GPU.
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subhamkhemka
commented on May 21, 2024
Working now, thanks @cdpierse
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Related Issues (20)
- What algorithm is used to visualize text in SequenceClassificationExplainer
- How to use transformers-interpret for sequencelabelling, for example layoutlmv3 or v3 HOT 1
- MultiLabelSequenceClassificationExplainer potentially bugged. HOT 14
- ImportError: cannot import name 'PairwiseSequenceClassificationExplainer' HOT 1
- How to interpret the model fine tuning on the pre-trained ViT model using the imagery with larger resolution (500 * 500) than the pre-trained dataset (224 * 224)
- Token Classification Memory Issue
- Issue using BertTokenizer (AttributeError) HOT 2
- 'Bert' object has no attribute 'config'
- Text attribution fails for XLM-Roberta models HOT 4
- Is it normal that attribution takes multiple seconds per text, even on a GPU? HOT 1
- ZeroShotClassificationExplainer appears to be broken
- Prediction differs from non-explainable evaluation HOT 1
- Output probability - SequenceClassificationExplainer
- Support for Summarization models HOT 3
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- Issue with Zero Shot Classifier
- How to use other types of transformers models? HOT 1
- Support for Reformer
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