integrate_text2text_model.sh

#!/bin/bash

# Script to integrate a text-to-text generation model into the Vishwamai model

# Step 1: Clone the repository
echo "Cloning the chat-agent repository..."
git clone https://github.com/VishwamAI/chat-agent.git
cd chat-agent

# Step 2: Install the required packages
echo "Installing required packages..."
pip install -r requirements.txt

# Step 3: Set up Hugging Face API token
echo "Setting up Hugging Face API token..."
export HUGGING_FACE_TOKEN=your_hugging_face_token

# Step 4: Clone the text-to-text generation model repository
echo "Cloning the google/flan-t5-base model repository..."
git clone https://huggingface.co/google/flan-t5-base

# Step 5: Integrate the model into the Vishwamai model
echo "Integrating the google/flan-t5-base model into the Vishwamai model..."
# Copy necessary files from the cloned model repository to the Vishwamai model directory
cp -r flan-t5-base/* vishwamai/

# Step 6: Update the Vishwamai model code to use the integrated model
echo "Updating the Vishwamai model code..."
# Modify the model.py file to include the integrated model
sed -i 's/from vishwamai.config import GemmaConfig, get_model_config/from vishwamai.config import VishwamaiConfig, get_model_config/' vishwamai/model.py
sed -i 's/class GemmaMLP(nn.Module):/class VishwamaiMLP(nn.Module):/' vishwamai/model.py
sed -i 's/class GemmaAttention(nn.Module):/class VishwamaiAttention(nn.Module):/' vishwamai/model.py
sed -i 's/class GemmaDecoderLayer(nn.Module):/class VishwamaiDecoderLayer(nn.Module):/' vishwamai/model.py
sed -i 's/class Gemma2DecoderLayer(nn.Module):/class Vishwamai2DecoderLayer(nn.Module):/' vishwamai/model.py
sed -i 's/class GemmaModel(nn.Module):/class VishwamaiModel(nn.Module):/' vishwamai/model.py
sed -i 's/class GemmaForCausalLM(nn.Module):/class VishwamaiForCausalLM(nn.Module):/' vishwamai/model.py

# Step 7: Update the README.md file
echo "Updating the README.md file..."
# Add instructions for using the integrated model
echo -e "\n## Using the Integrated Model\n\nTo use the integrated google/flan-t5-base model, follow the instructions below:\n\n1. Clone the repository:\n   \`\`\`\n   git clone https://github.com/VishwamAI/chat-agent.git\n   cd chat-agent\n   \`\`\`\n\n2. Install the required packages:\n   \`\`\`\n   pip install -r requirements.txt\n   \`\`\`\n\n3. Set up the Hugging Face API token:\n   \`\`\`\n   export HUGGING_FACE_TOKEN=your_hugging_face_token\n   \`\`\`\n\n4. Train the model:\n   \`\`\`\n   python scripts/train.py\n   \`\`\`\n\n5. Generate text:\n   \`\`\`\n   python scripts/generate_text.py --prompt \"Your prompt here\" --max_length 100\n   \`\`\`\n\n6. Evaluate the model:\n   \`\`\`\n   python scripts/evaluate.py --test_file path/to/test/file.txt\n   \`\`\`\n\n7. Test sampling parameters:\n   \`\`\`\n   python scripts/sampling_test.py --prompt \"Your prompt here\" --temperature 0.7 --top_p 0.9 --top_k 50\n   \`\`\`\n" >> README.md

# Step 8: Commit and push the changes
echo "Committing and pushing the changes..."
git add .
git commit -m "Integrated google/flan-t5-base model into Vishwamai model"
git push origin main

echo "Integration complete. Please review the changes and test the integrated model."