Update app.py

app.py

@@ -1,12 +1,16 @@
 import gradio as gr
-from transformers import pipeline
+import requests
 
-# Load the pipeline
-pipe = pipeline("text-generation", model="bigscience/bloom-560m")
+API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom-560m"
+headers = {"Authorization": "Bearer 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"}
+
+def query(payload):
+    response = requests.post(API_URL, headers=headers, json=payload)
+    return response.json()
 
-# Define a function to generate text using the pipeline
 def generate_text(prompt):
-    generated_text = pipe(prompt, max_length=100)[0]['generated_text']
+    output = query({"inputs": prompt})
+    generated_text = output[0]['generated_text']
     return generated_text
 
 # Create a Gradio interface