Add application file

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+from peft import PeftModel
+
+# Load base + LoRA fine-tuned model
+base_model = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
+adapter_model = "Noshitha98/TinyLlama-ToS-Finetuned"
+
+tokenizer = AutoTokenizer.from_pretrained(base_model)
+model = AutoModelForCausalLM.from_pretrained(base_model)
+model = PeftModel.from_pretrained(model, adapter_model)
+
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+def check_clause(text):
+    # Instruction prompt for anomaly detection
+    prompt = f"Detect unusual or risky clauses in this contract:\n\n{text}\n\nResponse:"
+    output = pipe(prompt, max_length=512, do_sample=False)[0]["generated_text"]
+    return output
+
+# Gradio UI
+iface = gr.Interface(
+    fn=check_clause,
+    inputs=gr.Textbox(lines=8, placeholder="Paste contract clause here..."),
+    outputs="text",
+    title="Contract Clause Checker",
+    description="Paste contract text to detect unusual or anomalous clauses using TinyLlama-ToS-Finetuned."
+)
+
+iface.launch()

requirements.txt

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+transformers
+peft
+torch
+gradio