Instructions to use Nech-C/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nech-C/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Nech-C/results") 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("Nech-C/results") model = AutoModelForImageClassification.from_pretrained("Nech-C/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e9b5e54d07ad801986d4915f9a92f717188f210ccdb0760861a15a9c49f26f0
- Size of remote file:
- 5.65 kB
- SHA256:
- ceb878ef93272fc88ce7a6bb6796e4a027a829964ff68ca7b6dcf54820c8e267
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