Create app.py

app.py

@@ -0,0 +1,24 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load model
+MODEL_NAME = "mistralai/Mistral-7B-Instruct-v0.3"
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, device_map="auto", torch_dtype=torch.float16)
+
+def generate(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    with torch.no_grad():
+        outputs = model.generate(**inputs, max_new_tokens=300)
+    text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return text
+
+# Gradio interface
+iface = gr.Interface(
+    fn=generate,
+    inputs=gr.Textbox(lines=5, placeholder="Enter your prompt here"),
+    outputs=gr.Textbox(label="AI Response"),
+)
+
+iface.launch(server_name="0.0.0.0", server_port=7860)