Qwen 2.5 72B Math Instruct
The largest model in the Qwen family of LLMs, tuned for math
Deploy Qwen 2.5 72B Math Instruct behind an API endpoint in seconds.
Deploy modelExample usage
Qwen uses the standard llama-style multi-turn messaging framework with system and user prompts.
Input
1import requests
2
3# Replace the empty string with your model id below
4model_id = ""
5baseten_api_key = os.environ["BASETEN_API_KEY"]
6
7data = {
8 "messages": [
9 {"role": "system", "content": "Please reason step by step, and put your final answer within \\boxed{}."},
10 {"role": "user", "content": "Find the value of $x$ that satisfies the equation $4x+5 = 6x+7$."},
11 ]
12 "stream": True,
13 "max_new_tokens": 512,
14 "temperature": 0.9
15}
16
17# Call model endpoint
18res = requests.post(
19 f"https://model-{model_id}.api.baseten.co/production/predict",
20 headers={"Authorization": f"Api-Key {baseten_api_key}"},
21 json=data,
22 stream=True
23)
24
25# Print the generated tokens as they get streamed
26for content in res.iter_content():
27 print(content.decode("utf-8"), end="", flush=True)JSON output
1[
2 "streaming",
3 "output",
4 "text"
5]
