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app.py

@@ -83,7 +83,7 @@ def respond(
     **kwargs,
 ):
     # prompt wrapper, only single-turn is allowed for now
-    prompt = f"### Human:\n{message}\n\n### Assistant:\n"
+    prompt = f"### Human:\n{instruction}\n\n### Assistant:\n"
     inputs = tokenizer(
         prompt,
         return_tensors="pt", 
@@ -129,7 +129,7 @@ g = gr.Interface(
         )
     ],
     title="ExpertLLaMA",
-    description="ExpertLLaMA is a open-source chatbot trained on expert instructed data produce with GPT-3.5, see our [project repo](https://github.com/OFA-Sys/ExpertLLaMA) for details.",
+    description="ExpertLLaMA is an open-source chatbot trained on expert-like data produced with GPT-3.5, see our [project repo](https://github.com/OFA-Sys/ExpertLLaMA) for details.",
 )
 g.queue(concurrency_count=1)
 g.launch()

requirements.txt

@@ -1,5 +1,4 @@
 torch
 transformers
 SentencePiece
-accelerate
-tqdm
+accelerate