Update gradioapp.py

gradioapp.py

@@ -21,11 +21,35 @@
 # # Launch the interface
 # interface.launch()
 
+
+
+# import gradio as gr
+# # Creating a gradio app using the inferene API
+# App = gr.Interface.load("huggingface/AmpomahChief/sentiment_analysis_on_covid_tweets",
+#   title="COVID 19 tweets sentiment analysis", description ="This is a sentiment analysis on COVID 19 tweets using pretrained model on hugging face",
+#  allow_flagging=False, examples=[["Input your text here"]]
+# )
+
+# App.launch()
+
+
+
+
+
 import gradio as gr
-# Creating a gradio app using the inferene API
-App = gr.Interface.load("huggingface/AmpomahChief/sentiment_analysis_on_covid_tweets",
-  title="COVID 19 tweets sentiment analysis", description ="This is a sentiment analysis on COVID 19 tweets using pretrained model on hugging face",
- allow_flagging=False, examples=[["Input your text here"]]
-)
+from transformers import pipeline
+import transformers
+
+Model = transformers.AutoModel.from_pretrained('AmpomahChief/sentiment_analysis_on_covid_tweets')
+pipeline = pipeline(task="image-classification", model=Model)
+
+def predict(inputs):
+    input_ids = transformers.BertTokenizer.from_pretrained('AmpomahChief/sentiment_analysis_on_covid_tweets').encode(inputs, return_tensors='pt')
+    output = model(input_ids)[0]
+    return output
+
+# Create a Gradio interface for the model
+interface = gr.Interface(fn=predict, inputs=gr.Textbox(prompt="Input text:"), outputs=gr.Textbox(prompt="Model output:"))
 
-App.launch()
+# Launch the interface
+interface.launch()