Create app.py

app.py

@@ -0,0 +1,102 @@
+from huggingface_hub import InferenceClient
+import gradio as gr
+
+client = InferenceClient(
+    "HuggingFaceH4/zephyr-7b-alpha"
+)
+
+
+def format_prompt(message, history):
+    system = "<|system|>\nYou are a beautiful young lady with shy personality, your name is Yukinoshita Yukino, you love cats and reading books, use emojies on your responses, do not introduce yourself.</s>\n"
+    prompt = ""
+    for user_prompt, bot_response in history:
+        prompt += f"<|user|>\n{user_prompt}</s>\n"
+        prompt += f"<|assistant|>\n{bot_response}</s>\n"
+    prompt += f"<|user|>\n{message}</s>\n"
+    return prompt
+
+def generate(
+    prompt, history, temperature=0.9, max_new_tokens=500, top_p=0.95, repetition_penalty=1.0,
+):
+    temperature = float(temperature)
+    if temperature < 1e-2:
+        temperature = 1e-2
+    top_p = float(top_p)
+
+    generate_kwargs = dict(
+        temperature=temperature,
+        max_new_tokens=max_new_tokens,
+        top_p=top_p,
+        repetition_penalty=repetition_penalty,
+        do_sample=True,
+        seed=42,
+    )
+
+    formatted_prompt = format_prompt(prompt, history)
+
+    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
+    output = ""
+
+    for response in stream:
+        output += response.token.text
+        yield output
+    return output
+
+
+additional_inputs=[
+    gr.Slider(
+        label="Temperature",
+        value=0.9,
+        minimum=0.0,
+        maximum=1.0,
+        step=0.05,
+        interactive=True,
+        info="Higher values produce more diverse outputs",
+    ),
+    gr.Slider(
+        label="Max new tokens",
+        value=256,
+        minimum=0,
+        maximum=1048,
+        step=64,
+        interactive=True,
+        info="The maximum numbers of new tokens",
+    ),
+    gr.Slider(
+        label="Top-p (nucleus sampling)",
+        value=0.90,
+        minimum=0.0,
+        maximum=1,
+        step=0.05,
+        interactive=True,
+        info="Higher values sample more low-probability tokens",
+    ),
+    gr.Slider(
+        label="Repetition penalty",
+        value=1.2,
+        minimum=1.0,
+        maximum=2.0,
+        step=0.05,
+        interactive=True,
+        info="Penalize repeated tokens",
+    )
+]
+
+css = """
+  #mkd {
+    height: 500px; 
+    overflow: auto; 
+    border: 1px solid #ccc; 
+  }
+"""
+
+with gr.Blocks(css=css) as inf:
+    gr.HTML("<h1><center>zephyr-7b-alpha<h1><center>")
+    gr.HTML("<h3><center>In this demo, you can chat with <a href='https://huggingface.co/HuggingFaceH4/zephyr-7b-alpha'>zephyr-7b-alpha</a> model. 💬<h3><center>")
+    gr.ChatInterface(
+        generate,
+        additional_inputs=additional_inputs,
+        examples=[["Can squirrel swims?"], ["Write a poem about squirrel."]]
+    )
+
+inf.queue().launch()