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")# pip install -U transformers accelerate # 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
Upload model
Browse files- config.json +1 -1
config.json
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"return_dict": true,
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"return_dict_in_generate": false,
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"scale_embedding": true,
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"sep_token_id":
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"suppress_tokens": null,
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"task_specific_params": null,
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"temperature": 1.0,
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"return_dict": true,
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"return_dict_in_generate": false,
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"scale_embedding": true,
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"sep_token_id": 75,
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"suppress_tokens": null,
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"task_specific_params": null,
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"temperature": 1.0,
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