Instructions to use Roy229/nml7324-image-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Roy229/nml7324-image-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Roy229/nml7324-image-classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Roy229/nml7324-image-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Compliance remediation: add model card README.md (MISSING_README)
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README.md
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---
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license: apache-2.0
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language:
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- en
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pipeline_tag: image-classification
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tags:
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- nml-registry
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- image-classifier
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library_name: transformers
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---
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# Image Classifier
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Classifies product photos into 1,200 fine-grained categories for the retail catalogue. Trained on an internal dataset of e-commerce images and deployed behind the catalogue search service. It is the highest-traffic model in the registry with roughly eight million inference requests per week.
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