Instructions to use influencer/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use influencer/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="influencer/model") 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("influencer/model") model = AutoModelForImageClassification.from_pretrained("influencer/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d04aab5e07941f6de4ddf391549c82a0ffe824ad6988cb5a6f9830e7eb4fb65
- Size of remote file:
- 4.98 kB
- SHA256:
- be588d1a9b625959af2ccf6469f542cc8046ee4c21e9299a042e72083fe10a25
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