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Climi/
Climate-Education-QA-Chatbot

Name: Climate-Education-QA-Chatbot
Availability: InStock

transformers

text2text-generation

text-generation-inference

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Generative QA Chatbot for Climate Education

This chatbot help users (especially students, young activists, or the general public) learn about climate change, its causes, impacts, solutions, and key concepts through conversational Q&A.

Model: T5-small (Text-To-Text Transfer Transformer)
Framework: TensorFlow
Evaluation Metrics: BLEU Score

Domain Justification:

Climate education chatbots address the critical need for accessible, accurate climate science information. Think of it like having a climate science teacher available 24/7 who can explain complex concepts like carbon cycles, greenhouse effects, or climate policies in simple terms.

Architecture Breakdown:

Architecture Type: Encoder-Decoder Transformer
Layers: 6 Encoder + 6 Decoder
Parameters: 60,506,624 (60M)
Size: ~240 MB
Performance: 0.0549 BLEU, ~17s generation
Attention Mechanism: Multi-Head Self-Attention
Position Encoding: Relative Position Bias
Activation Function: ReLU

Checkout the deployed QA chatbot on Streamlit Cloud: https://ayika-app-v1.streamlit.app/

Author: Eunice Adewusi Climiradi

My Links: https://linktr.ee/climiradi

Date: June 2025

Climi/Climate-Education-QA-Chatbot

Generative QA Chatbot for Climate Education

Domain Justification:

Architecture Breakdown:

Climi/
Climate-Education-QA-Chatbot