Instructions to use sirdug/Hand-Writing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sirdug/Hand-Writing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sirdug/Hand-Writing") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("sirdug/Hand-Writing") model = AutoModelForImageClassification.from_pretrained("sirdug/Hand-Writing", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from sirdug/Hand-Writing: direct link, hf CLI and curl.
- Browser
- Download file 524 Bytes
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https://huggingface.co/sirdug/Hand-Writing/resolve/main/README.md
- Command line
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hf download hf://sirdug/Hand-Writing/README.md
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curl -L -o README.md https://huggingface.co/sirdug/Hand-Writing/resolve/main/README.md
524 Bytes
| tags: | |
| - autotrain | |
| - image-classification | |
| widget: | |
| - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg | |
| example_title: Tiger | |
| - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg | |
| example_title: Teapot | |
| - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg | |
| example_title: Palace | |
| datasets: | |
| - mnist | |
| # Model Trained Using AutoTrain | |
| - Problem type: Image Classification | |
| ## Validation Metrics | |
| No validation metrics available | |