Instructions to use BeckerAnas/devout-voice-234 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BeckerAnas/devout-voice-234 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="BeckerAnas/devout-voice-234") 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("BeckerAnas/devout-voice-234") model = AutoModelForImageClassification.from_pretrained("BeckerAnas/devout-voice-234", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd08f93a23140dc62e1be82f6da7686691f2d5eb8d90c166d360fc40ad4095cb
- Size of remote file:
- 5.71 kB
- SHA256:
- 0db73a228985d421b1d78c66103e0a51e787ba8755136a7817634e9f921ea0f0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.