Create app.py

app.py

@@ -0,0 +1,16 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the LLaMA 3 model and tokenizer
+model_name = "kshabana/GOAT-llama3.1-v0.1"  # Replace with the actual model path if different
+model = AutoModelForCausalLM.from_pretrained(GOAT-llama3.1-v0.1-Q4_K_M.gguf)
+tokenizer = AutoTokenizer.from_pretrained(tokenizer.json)
+
+def generate_response(user_input):
+    inputs = tokenizer.encode(user_input, return_tensors="pt")
+    outputs = model.generate(inputs, max_length=50, num_return_sequences=1)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+interface = gr.Interface(fn=generate_response, inputs="text", outputs="text")
+interface.launch()