Spaces:
Sleeping
Sleeping
File size: 1,350 Bytes
6dae430 02ce4ee 19c180b 6dae430 19c180b 6dae430 02ce4ee 6dae430 19c180b 6dae430 02ce4ee 19c180b 6dae430 19c180b 6dae430 19c180b 6dae430 19c180b 6dae430 19c180b 6dae430 19c180b 02ce4ee 6dae430 19c180b 6dae430 19c180b |
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 57 58 59 |
import gradio as gr
import os
from huggingface_hub import InferenceClient
client = InferenceClient("explorewithai/Loxa-1.6B")
meo_system = os.environ.get("MEO")
def respond(
message,
history: list[tuple[str, str]],
max_tokens,
temperature,
top_p,
):
messages = [{"role": "system", "content": meo_system}]
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
messages.append({"role": "user", "content": message})
response = ""
for message in client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
token = message.choices[0].delta.content
response += token
yield response
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Slider(minimum=1, maximum=2048, value=2048, step=1, label="Max new tokens"),
gr.Slider(minimum=0.1, maximum=1.0, 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()
|