Instructions to use Flova/omr_transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Flova/omr_transformer 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="Flova/omr_transformer")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("Flova/omr_transformer") model = AutoModelForMultimodalLM.from_pretrained("Flova/omr_transformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e1b9b0f29a0bcc2057fed3c85666cdf3e6c7314498dce7e4cb8d9cb702e4c37
- Size of remote file:
- 574 MB
- SHA256:
- 9ed5c1b23e6dbda25aa8cb9281ef71b511a301256660d71dd013e5adb57de685
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