Instructions to use theoberva/UBCO-Model-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use theoberva/UBCO-Model-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="theoberva/UBCO-Model-v2") 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("theoberva/UBCO-Model-v2") model = AutoModelForImageClassification.from_pretrained("theoberva/UBCO-Model-v2") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:1b198335a1229d58139cf7e3b5f7a0e1355a8715f8f537fa3726dce43f18951c
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size 195914684
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