Instructions to use xxhwjzx/yanzheng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xxhwjzx/yanzheng with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="xxhwjzx/yanzheng") 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("xxhwjzx/yanzheng") model = AutoModelForImageClassification.from_pretrained("xxhwjzx/yanzheng", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Image Classification
Validation Metricsg
loss: nan
f1_macro: 0.19999999999999998
f1_micro: 0.42857142857142855
f1_weighted: 0.2571428571428571
precision_macro: 0.14285714285714285
precision_micro: 0.42857142857142855
precision_weighted: 0.18367346938775508
recall_macro: 0.3333333333333333
recall_micro: 0.42857142857142855
recall_weighted: 0.42857142857142855
accuracy: 0.42857142857142855
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