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app.py

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+
+# Load model directly
+from transformers import pipeline
+import gradio as gr
+import torch
+ 
+# Check if CUDA is available, otherwise use CPU
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+pipe = pipeline("text-generation", model="microsoft/BioGPT-Large", device=device)
+
+def question(message, history):
+
+
+    # Generate the response
+    response = pipe(message, max_length=200)[0]['generated_text'] 
+
+    return response
+
+#Description in Markdown
+description = """
+# Summary
+This chat directly pipes into this BioGPT Large LLM.  This LLM outputs some strange things and can be found here: [Microsoft BioGPT Large](https://huggingface.co/microsoft/BioGPT-Large). To use this LLM and derive any value, think of it as a neural network trying to complete a problem. See the examples for ideas.
+
+### Examples
+* HIV is
+* Foot Fungus causes
+* Symptoms of liver failure are
+
+### Good Luck! 🍀
+Coded 🧾 by [Matthew Rogers](https://matthewrogers.org) | [RamboRogers](https://github.com/ramboRogers)
+"""
+
+
+
+program = gr.ChatInterface(question,description=description,title="Microsoft BioGPT Large Chat")
+
+if __name__ == "__main__":
+    program.launch()

requirements.txt

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+sacremoses
+transformers
+gradio
+torch