Algebra T5 Model
Model Description
This model is a fine-tuned version of FLAN-T5 designed to generate explanations and responses related to school-level algebra concepts.
The model was trained on instructional algebra content and exercises to help generate explanations, examples, and basic reasoning about algebra topics commonly encountered in secondary education.
The goal of the model is to support experimentation with AI-assisted explanations for introductory algebra topics.
Model Details
- Developed by: Shaif Chowdhury
- Model type: Sequence-to-sequence text generation
- Base model:
google/flan-t5-base - Language: English
- Domain: School algebra / mathematics education
- License: Apache 2.0 (same as base model)
Intended Use
Direct Use
This model can be used for:
- Explaining algebra concepts
- Generating short algebra explanations
- Producing educational responses related to school algebra
- Experimentation with AI-assisted math tutoring
Example tasks:
- Explain algebra
- Describe algebra concepts
- Generate simple explanations of algebra topics
Example Usage
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("USERNAME/algebra-t5-model")
model = AutoModelForSeq2SeqLM.from_pretrained("USERNAME/algebra-t5-model")
prompt = "explain algebra"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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