File size: 1,472 Bytes
4d56e70
 
640a262
4d56e70
 
 
 
 
23eecb9
 
640a262
4d56e70
 
 
 
 
 
 
 
640a262
 
 
 
 
4d56e70
 
 
640a262
 
 
 
4d56e70
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
import gradio as gr
from huggingface_hub import InferenceClient
import spaces

"""
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
"""

client = InferenceClient()
model = "veechan/gpt-neo-1.3B-platypus-finetuned"
@spaces.GPU
def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    # Construct the prompt
    prompt = system_message + "\n\n"
    for user_msg, bot_msg in history:
        prompt += f"Human: {user_msg}\nAI: {bot_msg}\n"
    prompt += f"Human: {message}\nAI:"

    response = ""

    for token in client.text_generation(
        prompt,
        model=model,
        max_new_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p,
    ):
        response += token
        yield response

demo = gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(
            minimum=0.1,
            maximum=1.0,
            value=0.95,
            step=0.05,
            label="Top-p (nucleus sampling)",
        ),
    ],
)

if __name__ == "__main__":
    demo.launch()