Image Classification
Transformers
Safetensors
timm
timm_wrapper
vision
trackio
Generated from Trainer
Instructions to use evalstate/ic-smoke-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use evalstate/ic-smoke-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="evalstate/ic-smoke-test") 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("evalstate/ic-smoke-test") model = AutoModelForImageClassification.from_pretrained("evalstate/ic-smoke-test") - timm
How to use evalstate/ic-smoke-test with timm:
import timm model = timm.create_model("hf_hub:evalstate/ic-smoke-test", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b6a39a0db51779fcb534a319d70d296da5f92a6a96f5cde369248f0797d3ce1
- Size of remote file:
- 5.27 kB
- SHA256:
- e078e04293975ba47a8c39135e7d601658ca5bf0498370700501a828f5b41ec2
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