Spaces:
Running on Zero
Running on Zero
File size: 2,626 Bytes
ddc3343 0ce785f ddc3343 0ce785f ddc3343 | 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 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 | import spaces # noqa: F401 must be imported before torch
import torch
import gradio as gr
from threading import Thread
from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
MODEL_ID = "Qwen/Qwen2.5-Coder-3B-Instruct"
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
model = AutoModelForCausalLM.from_pretrained(
MODEL_ID,
torch_dtype=torch.bfloat16,
attn_implementation="sdpa",
).to("cuda").eval()
@spaces.GPU(duration=60)
def respond(
message: str,
history: list[dict[str, str]],
system_message: str,
max_tokens: int,
temperature: float,
top_p: float,
) -> str:
"""Generate a reply from the coding assistant, streaming it token by token."""
messages = [{"role": "system", "content": system_message}]
messages += history
messages.append({"role": "user", "content": message})
# apply_chat_template returns a BatchEncoding on new transformers, a tensor on old
ids = tokenizer.apply_chat_template(
messages, add_generation_prompt=True, return_tensors="pt"
)
input_ids = (ids["input_ids"] if not torch.is_tensor(ids) else ids).to("cuda")
streamer = TextIteratorStreamer(
tokenizer, skip_prompt=True, skip_special_tokens=True
)
gen_kwargs = dict(
input_ids=input_ids, streamer=streamer, max_new_tokens=max_tokens
)
if temperature > 0.1:
gen_kwargs.update(do_sample=True, temperature=temperature, top_p=top_p)
else:
gen_kwargs.update(do_sample=False)
Thread(target=model.generate, kwargs=gen_kwargs, daemon=True).start()
response = ""
for new_text in streamer:
response += new_text
yield response
demo = gr.ChatInterface(
fn=respond,
title="Small Code Assistant",
description="Qwen2.5-Coder-3B-Instruct streaming on ZeroGPU.",
additional_inputs=[
gr.Textbox(
value="You are a helpful coding assistant.", label="System message"
),
gr.Slider(
minimum=64, maximum=2048, value=512, step=64, label="Max new tokens"
),
gr.Slider(
minimum=0.0, maximum=2.0, 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"
),
],
examples=[
["Write a Python function that checks if a string is a palindrome."],
["Explain what this regex does: ^\\d{3}-\\d{4}$"],
["Fix the bug: `for i in range(len(items)): print(items[i+1])`"],
],
cache_examples=False,
)
if __name__ == "__main__":
demo.launch(mcp_server=True)
|