Instructions to use IIC/MEL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/MEL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="IIC/MEL")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("IIC/MEL") model = AutoModel.from_pretrained("IIC/MEL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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## Acknowledgements
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This work has received funding from the <a src="https://inesdata-project.eu/content/en/index.html"> (Infrastructure to Investigate Data Spaces in Distributed
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Environments at UPM), a project funded under the UNICO I+D CLOUD call by the Ministry for Digital Transformation
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and the Civil Service, in the framework of the recovery plan PRTR financed by the European Union (NextGenerationEU)
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## Acknowledgements
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This work has received funding from the <a src="https://inesdata-project.eu/content/en/index.html"> Inesdata-project </a> (Infrastructure to Investigate Data Spaces in Distributed
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Environments at UPM), a project funded under the UNICO I+D CLOUD call by the Ministry for Digital Transformation
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and the Civil Service, in the framework of the recovery plan PRTR financed by the European Union (NextGenerationEU)
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