Instructions to use Zul001/HydroSense_Gemma_Finetuned_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zul001/HydroSense_Gemma_Finetuned_Model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Zul001/HydroSense_Gemma_Finetuned_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Verified signature# Fine_Tuned_Gemma_Model_on_Water_Dataset This Gemma 2B model has been fine-tuned on a comprehensive waste and stormwater dataset to facilitate advanced resource management, efficient allocation, and accelerated decision-making in the field of environmental engineering. The specialized model leverages the powerful base architecture of Gemma 7B, originally developed by Google, and adapts it to the specific needs of waste and stormwater management. Key features of this fine-tuned model include: * Domain-Specific Knowledge: Trained on extensive waste and stormwater data, including treatment processes, infrastructure details, and environmental impact assessments. * Resource Optimization: Capable of analyzing complex data to suggest optimal resource allocation strategies for waste treatment facilities and stormwater management systems. * Predictive Analytics: Utilizes historical data and current inputs to forecast potential issues, such as overflow events or treatment capacity shortages. *…5c315e4 -
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