integrate_text_to_text_features.sh

#!/bin/bash

# Script to integrate text-to-text generation features from MTL-data-to-text model into Vishwamai model

# Ensure the script is executed from the root of the repository
cd "$(dirname "$0")"

# Activate the virtual environment
source venv/bin/activate

# Install the Transformers library if not already installed
pip install transformers

# Download the pre-trained MTL-data-to-text model and tokenizer
python - <<EOF
from transformers import MvpTokenizer, MvpForConditionalGeneration

tokenizer = MvpTokenizer.from_pretrained("RUCAIBox/mvp")
model = MvpForConditionalGeneration.from_pretrained("RUCAIBox/mtl-data-to-text")

# Save the tokenizer and model
tokenizer.save_pretrained("vishwamai/tokenizer")
model.save_pretrained("vishwamai/model")
EOF

# Adapt the Vishwamai model's code to incorporate the MTL-data-to-text model's tokenizer and generation methods
# This step may require manual intervention to modify the input and output processing to match the MTL-data-to-text model's expected formats

# Fine-tune the integrated model on the user's specific dataset
# Ensure the dataset is available in the `datasets` directory
python scripts/train_t5.py --config configs/config_for_9b.yaml

# Deactivate the virtual environment
deactivate