Instructions to use vanshp123/ocrmnist with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vanshp123/ocrmnist with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="vanshp123/ocrmnist")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("vanshp123/ocrmnist") model = AutoModelForImageTextToText.from_pretrained("vanshp123/ocrmnist") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad42f13df62db210697d93a7839da99221544d3cc8e1c9a0561aa73a00d4975a
- Size of remote file:
- 1.54 GB
- SHA256:
- ef223095ba724a5acb806d2af568556255d3421acf244b09bb77876e153e1453
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