create app.py

app.py

@@ -0,0 +1,19 @@
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+import torch  
+import gradio as gr  
+
+# Load model and tokenizer from Hugging Face directly
+model_name = "deepseek-ai/deepseek-7b-instruct"  
+tokenizer = AutoTokenizer.from_pretrained(model_name)  
+model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto")  
+
+# Create a simple chat function  
+def chat_function(prompt):  
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)  
+    outputs = model.generate(**inputs, max_length=200)  
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)  
+    return response  
+
+# Build a simple Gradio interface  
+iface = gr.Interface(fn=chat_function, inputs="text", outputs="text")  
+iface.launch()