README.md

metadata

language: en
tags:
  - question-answering
  - science
  - flan-t5
  - transformers
license: mit

Science Q&A Base Model

This is a base model model fine-tuned for science question answering.

Model Details

• Base Model: google/flan-t5-small
• Task: Question Answering
• Domain: Science
• Training Data: Science content from PDF documents
• Model Type: Base Model

Usage

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("alexputhiyadom/science-qa-base")
model = AutoModelForSeq2SeqLM.from_pretrained("alexputhiyadom/science-qa-base")

# Example usage
question = "What is science?"
inputs = tokenizer(f"Question: {question}\nAnswer:", return_tensors="pt")
outputs = model.generate(**inputs, max_length=128)
answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(answer)

Training

This model was trained on science content using the flan-t5-small base model. The training focused on generating concise, accurate answers to science-related questions.

License

MIT License