Instructions to use theophilusijiebor1/Text2Image_PyData_23 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use theophilusijiebor1/Text2Image_PyData_23 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="theophilusijiebor1/Text2Image_PyData_23") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("theophilusijiebor1/Text2Image_PyData_23") model = AutoModelForImageClassification.from_pretrained("theophilusijiebor1/Text2Image_PyData_23") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 971cdafd6e0f9dd501dce55ffe863d5949cf212d73da02a9a0642e5faa5a4a4c
- Size of remote file:
- 4.54 kB
- SHA256:
- d5bc8d3499dfc1c5151ec1407658c285dabd5da08a82a3c8d87fbd806abe3abb
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