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qwen3

Runnable Python SDK example qwen3.

from mistralrs import Runner, Which, ChatCompletionRequest, MultimodalArchitecture
# Non-MoE model
runner = Runner(
which=Which.MultimodalPlain(
model_id="https://huggingface.co/Qwen/Qwen3-4B",
arch=MultimodalArchitecture.Qwen3,
),
in_situ_quant="Q4K",
)
# MoE model
# runner = Runner(
# which=Which.MultimodalPlain(
# model_id="https://huggingface.co/Qwen/Qwen3-30B-A3B",
# arch=MultimodalArchitecture.Qwen3Moe,
# ),
# in_situ_quant="Q4K",
# )
messages = [
{
"role": "user",
"content": "Hello! How many rs in strawberry?",
},
]
# ------------------------------------------------------------------
# First question, thinking mode is enabled by default
# ------------------------------------------------------------------
completion = runner.send_chat_completion_request(
ChatCompletionRequest(
model="default",
messages=messages,
max_tokens=1024,
frequency_penalty=1.0,
top_p=0.1,
temperature=0,
)
)
resp = completion.choices[0].message.content
print(resp)
messages.append({"role": "assistant", "content": completion.choices[0].message.content})
messages = [
{
"role": "user",
"content": "How many rs in blueberry? /no_think",
},
]
# ------------------------------------------------------------------
# Second question, disable thinking mode with explicit or /no_think
# ------------------------------------------------------------------
completion = runner.send_chat_completion_request(
ChatCompletionRequest(
model="default",
messages=messages,
max_tokens=1024,
frequency_penalty=1.0,
top_p=0.1,
temperature=0,
# enable_thinking=False
)
)
resp = completion.choices[0].message.content
print(resp)
messages.append({"role": "assistant", "content": completion.choices[0].message.content})
messages = [
{
"role": "user",
"content": "Are you sure? /think",
},
]
# ------------------------------------------------------------------
# Third question, reenable thinking mode with explicit or /think
# ------------------------------------------------------------------
completion = runner.send_chat_completion_request(
ChatCompletionRequest(
model="default",
messages=messages,
max_tokens=1024,
frequency_penalty=1.0,
top_p=0.1,
temperature=0,
# enable_thinking=False
)
)
resp = completion.choices[0].message.content
print(resp)

Source: examples/python/qwen3.py