Instructions to use lukasec/Maverick-Midas with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lukasec/Maverick-Midas with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lukasec/Maverick-Midas")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lukasec/Maverick-Midas") model = AutoModelForSequenceClassification.from_pretrained("lukasec/Maverick-Midas", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Create README.md
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README.md
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# Maverick-Midas
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MAV-Moneyball is a submodel of [**Maverick**](https://huggingface.co/lukasec/Maverick) - please refer to its model card for further information.<br>
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Developed in my internship at [**Vela Partners**](https://vela.partners/) as a Machine Learning Engineer. <br>
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The paper presenting Maverick can be found on my [GitHub](https://github.com/lukasec/Maverick). <br>
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