Create app.py

app.py

@@ -0,0 +1,17 @@
+import torch
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("upstage/SOLAR-10.7B-Instruct-v1.0")
+model = AutoModelForCausalLM.from_pretrained("upstage/SOLAR-10.7B-Instruct-v1.0")
+
+def generate_response(prompt):
+    conversation = [{'role': 'user', 'content': prompt}]
+    prompt = tokenizer.apply_chat_template(conversation, tokenizer=False, add_generation_prompt=True)
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    outputs = model.generate(**inputs, use_cache=True, max_length=4096)
+    outputs_text = tokenizer.decode(outputs[0])
+    return outputs_text
+
+iface = gr.Interface(fn=generate_response, inputs="text", outputs="text")
+iface.launch()