Instructions to use Johnson8187/Vision_or_not with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Johnson8187/Vision_or_not with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Johnson8187/Vision_or_not")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Johnson8187/Vision_or_not") model = AutoModelForSequenceClassification.from_pretrained("Johnson8187/Vision_or_not", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7112bfa310d7ffd3f7c084ced440da0b2e75a6c4165922b30e046a047685d81c
- Size of remote file:
- 17.1 MB
- SHA256:
- 3ea2d57e1ab5ebb5789b8e8e6f9593a996e8b624f870e6f55f63abe5359ff32c
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