Create app.py

app.py

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+from transformers import pipeline
+import gradio as gr
+
+model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1",torch_dtype=torch.float16, device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1")
+
+def generate(message):
+    text = f"You are an assistant to help people with suicide toughts and their family and friends. Given a sentence you will classify it into three categories: suicide intent, if the sentence belongs that has a suicide intent or have suicidal toughts; information, if the sentence belongs to a person that is looking for information about suicide or is concern about some relative; or depression, if the sentence belongs to a person that is depressed or have negative toughts. Classify with just one word the sentence {message} and give an explanation in Spanish"
+
+    messages = [
+        {"role": "user", "content": text},
+    ]
+
+    encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")
+
+    model_inputs = encodeds.to(device)
+    model.to(device)
+
+    generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
+    decoded = tokenizer.batch_decode(generated_ids)
+    print(decoded[0][decoded[0].rfind(["[/INST]"])+6:])
+
+
+example1 = "No quiero seguir viviendo ¿qué puedo hacer?."
+example2 = "¿Cómo puedo ayudar a un amigo que quiere quitarse la vida?"
+
+    
+
+iface = gr.Interface(fn=information_or_intent,inputs="text", outputs="text",examples=[example1,example2]).launch(share=False)