Update app.py

app.py

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+
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+import os
+import torch
+from datasets import load_dataset
+from transformers import (
+    AutoModelForCausalLM,
+    AutoTokenizer,
+    BitsAndBytesConfig,
+    HfArgumentParser,
+    TrainingArguments,
+    pipeline,
+    logging,
+)
+from peft import LoraConfig, PeftModel
+# from trl import SFTTrainer
+
+tokenizer = AutoTokenizer.from_pretrained("Gbssreejith/new_TinyLlama3")
+model = AutoModelForCausalLM.from_pretrained("Gbssreejith/new_TinyLlama3")
+
+def generate_response(prompt):
+    pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=50)
+    result = pipe(f"<s>[INST] {prompt} [/INST]")
+    return result[0]['generated_text']
+
+iface = gr.Interface(
+    fn=generate_response,
+    inputs="text",
+    outputs="text",
+    title="Text Generation",
+    description="Enter a prompt and get a generated response.",
+    examples=[
+        ["I'm having trouble sleeping. Any advice?"],
+        ["I sad i dont know what to do"]
+    ]
+)
+
+iface.launch(share=True,debug=True)