inital app

app.py

@@ -0,0 +1,45 @@
+import gradio as gr
+from transformers import pipeline
+
+gbert_pipeline = pipeline("text-classification", model="LennardZuendorf/bert-base-german-cased", top_k=None, token="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")
+leolm_pipeline = pipeline("text-classification", model="LennardZuendorf/interpretor", top_k=None, token="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")
+chat_pipeline = pipeline("conversational", model="meta-llama/Llama-2-7b-chat-hf", top_k=None, token="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")
+
+with gr.Blocks() as ui:
+    with gr.Row():
+        gr.Markdown(
+            """
+            # Thesis Model Demos
+            Select between tabs below for try the different models.
+            """)
+    with gr.Tab("GBERT HateSpeech Detection"):
+        with gr.Row():
+            gr.Markdown(
+                """
+                ### GBERT (German Language BERT by Deepset) Demo
+                #### Model finetuned on German Hate Speech dataset (~3,5k sequences)
+                """)
+        with gr.Row():
+            gr.Interface.from_pipeline(gbert_pipeline)
+
+    with gr.Tab("LeoLM HateSpeech Detection"):
+        with gr.Row():
+            gr.Markdown(
+                """
+                ### LeoLM (German Language FineTuned LlaMa2 Model) Demo
+                #### Model finetuned on German Hate Speech dataset (~3,5k sequences)
+                """)
+        with gr.Row():
+            gr.Button("New Tiger")
+
+    with gr.Tab("Chat Model Interface"):
+        with gr.Row():
+            gr.Markdown(
+                """
+                ### LlaMa 2 Chat Demo
+                """)
+        with gr.Row():
+            gr.Interface.from_pipeline(chat_pipeline)
+
+if __name__ == "__main__":
+    ui.launch()