Add initial implementation of Streamlit app for fine-tuned Phi-2 model demo with .gitignore and requirements

.gitignore

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+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Virtual Environment
+venv/
+env/
+ENV/
+.env
+.venv
+
+# IDE
+.idea/
+.vscode/
+*.swp
+*.swo
+.project
+.pydevproject
+.settings
+
+# Jupyter Notebook
+.ipynb_checkpoints
+*.ipynb_checkpoints/
+
+# PyTorch
+*.pth
+*.pt
+*.pkl
+
+# Logs and databases
+*.sqlite
+*.db
+
+# OS generated files
+.DS_Store
+.DS_Store?
+._*
+.Spotlight-V100
+.Trashes
+ehthumbs.db
+Thumbs.db
+
+# Project specific
+runs/
+checkpoints/
+outputs/
+logs/ 
+lightning_logs/

app.py

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+import streamlit as st
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+from peft import PeftModel
+from huggingface_hub import snapshot_download
+
+# Page configuration
+st.set_page_config(page_title="Fine-tuned Phi-2 Demo", page_icon="🤖", layout="wide")
+
+# Streamlit UI
+st.title("Fine-tuned Phi-2 Model Demo")
+st.markdown(
+    """
+This app demonstrates a fine-tuned version of Microsoft's Phi-2 model.
+Enter your prompt below and see the model generate text!
+"""
+)
+
+
+@st.cache_resource
+def load_model():
+    with st.status("Loading model from Hugging Face...", expanded=True) as status:
+        st.write("Downloading checkpoint files...")
+        # Download the checkpoint files from your HF repo
+        model_repo = "Adityak204/phi2-finetuned-checkpoint"
+        checkpoint_path = snapshot_download(repo_id=model_repo)
+
+        st.write("Loading base model...")
+        # Load the base model
+        base_model = AutoModelForCausalLM.from_pretrained(
+            "microsoft/phi-2",
+            torch_dtype=torch.float16,
+            device_map="auto",
+            trust_remote_code=True,
+        )
+
+        st.write("Loading LoRA adapter weights...")
+        # Load the LoRA adapter weights
+        model = PeftModel.from_pretrained(
+            base_model, checkpoint_path, device_map="auto"
+        )
+
+        st.write("Loading tokenizer...")
+        # Load tokenizer
+        tokenizer = AutoTokenizer.from_pretrained(checkpoint_path)
+        tokenizer.pad_token = tokenizer.eos_token
+
+        st.write("Creating text generation pipeline...")
+        # Create text generation pipeline
+        pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer)
+
+        status.update(
+            label="Model loaded successfully!", state="complete", expanded=False
+        )
+
+        return pipe
+
+
+# Load the model and pipeline (cached to avoid reloading)
+pipe = load_model()
+
+# Input form
+with st.form("generation_form"):
+    prompt = st.text_area(
+        "Enter your prompt:",
+        height=150,
+        placeholder="Example: What is the square root of 81?",
+    )
+
+    max_length = st.slider(
+        "Maximum length:",
+        min_value=32,
+        max_value=1024,
+        value=256,
+        step=32,
+        help="Maximum number of tokens to generate",
+    )
+
+    generate_button = st.form_submit_button("Generate")
+
+# Generate text when button is clicked
+if generate_button and prompt:
+    with st.spinner("Generating..."):
+        # Generate text
+        prompt = f"""
+        ### prompter: {prompt}
+        ### assistant:
+        """
+        generated_text = pipe(
+            prompt,
+            max_length=max_length,
+            do_sample=True,
+            num_return_sequences=1,
+        )[0]["generated_text"]
+
+        # Display the result
+        st.subheader("Generated Output:")
+        st.write(generated_text)
+
+        # Copy button
+        st.text_area("Copy output:", value=generated_text, height=150)
+
+# Sidebar with model information
+with st.sidebar:
+    st.header("About This Model")
+    st.write(
+        """
+    This is a fine-tuned version of Microsoft's Phi-2 model.
+    
+    The model was fine-tuned using QLoRA techniques to improve its performance on specific tasks.
+    
+    Original model: [microsoft/phi-2](https://huggingface.co/microsoft/phi-2)
+    
+    Fine-tuned model: [Adityak204/phi2-finetuned-checkpoint](https://huggingface.co/Adityak204/phi2-finetuned-checkpoint)
+    """
+    )
+
+# Footer
+st.markdown("---")
+st.markdown("Powered by a fine-tuned version of Microsoft's Phi-2 model")

requirements.txt

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+streamlit==1.28.0
+torch>=2.0.0
+transformers>=4.34.0
+accelerate>=0.20.0
+peft>=0.4.0
+bitsandbytes>=0.40.0
+huggingface-hub>=0.17.0