AI for Community Climate Action
Explore our secure, transparent, and green pipeline for training a large language model to coordinate and accelerate global climate solutions.
How It Works
Data Collection
Gathering diverse climate action data from various sources.
Model Training
Training the LLM on collected data using green computing practices.
Deployment
Deploying the model for community use and feedback.
Reporting
Generating reports on model performance and impact.
Our Core Principles
Comprehensive Security
Ensuring data privacy and model security throughout the pipeline.
Green Computing
Minimizing environmental impact through energy-efficient training methods.
Transparency and Efficacy
Providing clear insights into model workings and performance metrics.
ClimateGPT
Community action model trained on Clima-500 and others
Finetuned and RAG-enabled for community and policy responsibilities. Fine-tune the way you want.
The dataset matters, and up-to-date APIs to fetch real-time and factual data are crucial.
Community Response & Actions
We use RAG with custom state-wise data to ground conversations and generate community-based responses and actions.
- Get localized insights for your state and city
- See responsible stakeholders and proposed actions
- Coordinate with community groups and policymakers
Question: Who do you think is responsible, and how can we tackle this beyond the actions above?