modelscope / modelscope/ms-swift

How to run Qwen3.5 9B GRPO GSM8K

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  • I have searched existing issues, and this is a new question or discussion topic. / 我已经搜索过现有的 issues,确认这是一个新的问题与讨论。
Question Description / 问题描述

I want to train Qwen3.5 9B using the GRPO method on the GSM8K dataset, but I am encountering an error.
I am unable to install causal_conv1d.

Here is pip list:
Package Version


absl-py 2.4.0
accelerate 1.14.0
addict 2.4.0
aiofiles 24.1.0
aiohappyeyeballs 2.6.2
aiohttp 3.14.1
aiosignal 1.4.0
aliyun-python-sdk-core 2.16.0
aliyun-python-sdk-kms 2.16.5
annotated-doc 0.0.4
annotated-types 0.7.0
anthropic 0.109.1
antlr4-python3-runtime 4.13.2
anyio 4.13.0
apache-tvm-ffi 0.1.9
astor 0.8.1
attrdict 2.0.1
attrs 26.1.0
av 17.1.0
binpacking 2.0.1
blake3 1.0.8
brotli 1.2.0
cachetools 7.1.4
cbor2 6.1.2
certifi 2026.5.20
cffi 2.0.0
charset-normalizer 3.4.7
click 8.4.1
cloudpickle 3.1.2
compressed-tensors 0.17.0
contourpy 1.3.3
cpm-kernels 1.0.11
crcmod 1.7
cryptography 49.0.0
cuda-bindings 13.3.1
cuda-core 1.0.1
cuda-pathfinder 1.5.5
cuda-python 13.3.1
cuda-tile 1.3.0
cuda-toolkit 13.0.2
cycler 0.12.1
dacite 1.9.2
datasets 4.8.4
deepspeed 0.19.1
depyf 0.20.0
detect-installer 0.1.0
dill 0.4.1
diskcache 5.6.3
distro 1.9.0
dnspython 2.8.0
docstring_parser 0.18.0
einops 0.8.2
email-validator 2.3.0
fastapi 0.136.3
fastapi-cli 0.0.24
fastapi-cloud-cli 0.20.0
fastar 0.11.0
fastsafetensors 0.3.2
ffmpy 1.0.0
filelock 3.29.4
fla-core 0.5.0
flash_attn 2.8.3
flash-linear-attention 0.5.0
flashinfer-cubin 0.6.12
flashinfer-python 0.6.12
fonttools 4.63.0
frozenlist 1.8.0
fsspec 2026.2.0
gguf 0.19.0
googleapis-common-protos 1.75.0
gradio 5.50.0
gradio_client 1.14.0
groovy 0.1.2
grpcio 1.81.1
h11 0.16.0
hf-xet 1.5.1
hjson 3.1.0
httpcore 1.0.9
httptools 0.8.0
httpx 0.28.1
httpx-sse 0.4.3
huggingface_hub 1.19.0
humming-kernels 0.1.4
idna 3.18
ijson 3.5.0
importlib_metadata 9.0.0
interegular 0.3.3
Jinja2 3.1.6
jiter 0.15.0
jmespath 0.10.0
joblib 1.5.3
json_repair 0.60.1
jsonschema 4.26.0
jsonschema-specifications 2025.9.1
kiwisolver 1.5.0
lark 1.2.2
latex2sympy2_extended 1.0.6
liger_kernel 0.8.0
llguidance 1.7.6
llvmlite 0.47.0
lm-format-enforcer 0.11.3
loguru 0.7.3
Markdown 3.10.2
markdown-it-py 4.2.0
MarkupSafe 3.0.3
math-verify 0.5.2
matplotlib 3.11.0
mcp 1.27.2
mdurl 0.1.2
mistral_common 1.11.3
ml_dtypes 0.5.4
model-hosting-container-standards 0.1.15
modelscope 1.37.1
mpmath 1.3.0
ms_swift 4.3.0
msgpack 1.2.0
msgspec 0.21.1
multidict 6.7.1
multiprocess 0.70.19
networkx 3.6.1
ninja 1.13.0
nltk 3.9.4
numba 0.65.0
numpy 2.3.5
nvidia-cublas 13.1.0.3
nvidia-cublas-cu12 12.8.3.14
nvidia-cuda-cccl 13.3.3.3.1
nvidia-cuda-crt 13.3.33
nvidia-cuda-cupti 13.0.85
nvidia-cuda-cupti-cu12 12.8.57
nvidia-cuda-nvcc 13.2.78
nvidia-cuda-nvrtc 13.0.88
nvidia-cuda-nvrtc-cu12 12.8.61
nvidia-cuda-runtime 13.0.96
nvidia-cuda-runtime-cu12 12.8.57
nvidia-cuda-tileiras 13.2.78
nvidia-cudnn-cu12 9.7.1.26
nvidia-cudnn-cu13 9.19.0.56
nvidia-cudnn-frontend 1.25.0
nvidia-cufft 12.0.0.61
nvidia-cufft-cu12 11.3.3.41
nvidia-cufile 1.15.1.6
nvidia-cufile-cu12 1.13.0.11
nvidia-curand 10.4.0.35
nvidia-curand-cu12 10.3.9.55
nvidia-cusolver 12.0.4.66
nvidia-cusolver-cu12 11.7.2.55
nvidia-cusparse 12.6.3.3
nvidia-cusparse-cu12 12.5.7.53
nvidia-cusparselt-cu12 0.6.3
nvidia-cusparselt-cu13 0.8.0
nvidia-cutlass-dsl 4.5.2
nvidia-cutlass-dsl-libs-base 4.5.2
nvidia-cutlass-dsl-libs-cu13 4.5.2
nvidia-ml-py 13.610.43
nvidia-nccl-cu12 2.26.2
nvidia-nccl-cu13 2.28.9
nvidia-nvjitlink 13.0.88
nvidia-nvjitlink-cu12 12.8.61
nvidia-nvshmem-cu13 3.4.5
nvidia-nvtx 13.0.85
nvidia-nvtx-cu12 12.8.55
nvidia-nvvm 13.2.78
openai 2.41.1
openai-harmony 0.0.8
opencv-python-headless 4.13.0.92
opentelemetry-api 1.42.1
opentelemetry-exporter-otlp 1.42.1
opentelemetry-exporter-otlp-proto-common 1.42.1
opentelemetry-exporter-otlp-proto-grpc 1.42.1
opentelemetry-exporter-otlp-proto-http 1.42.1
opentelemetry-proto 1.42.1
opentelemetry-sdk 1.42.1
opentelemetry-semantic-conventions 0.63b1
opentelemetry-semantic-conventions-ai 0.5.1
orjson 3.11.9
oss2 2.19.1
outlines_core 0.2.14
packaging 26.0
pandas 2.3.3
partial-json-parser 0.2.1.1.post7
peft 0.19.1
pillow 11.3.0
pip 26.1.1
prometheus_client 0.25.0
prometheus-fastapi-instrumentator 8.0.0
propcache 0.5.2
protobuf 6.33.6
psutil 7.2.2
py-cpuinfo 9.0.0
pyarrow 24.0.0
pybase64 1.4.3
pycountry 26.2.16
pycparser 3.0
pycryptodome 3.23.0
pydantic 2.12.3
pydantic_core 2.41.4
pydantic-extra-types 2.11.1
pydantic-settings 2.14.1
pydub 0.25.1
pyelftools 0.33
Pygments 2.20.0
PyJWT 2.13.0
pyparsing 3.3.2
python-dateutil 2.9.0.post0
python-dotenv 1.2.2
python-json-logger 4.1.0
python-multipart 0.0.32
pytz 2026.2
PyYAML 6.0.3
pyzmq 27.1.0
quack-kernels 0.5.0
qwen-vl-utils 0.0.14
referencing 0.37.0
regex 2026.5.9
requests 2.34.2
rich 15.0.0
rich-toolkit 0.20.1
rignore 0.7.6
rouge 1.0.1
rpds-py 2026.5.1
ruff 0.15.17
safehttpx 0.1.7
safetensors 0.8.0
scipy 1.17.1
semantic-version 2.10.0
sentencepiece 0.2.1
sentry-sdk 2.62.0
setproctitle 1.3.7
setuptools 80.10.2
shellingham 1.5.4
simplejson 4.1.1
six 1.17.0
sniffio 1.3.1
sortedcontainers 2.4.0
sse-starlette 3.4.4
starlette 1.3.1
supervisor 4.3.0
sympy 1.14.0
tabulate 0.10.0
tensorboard 2.20.0
tensorboard-data-server 0.7.2
tiktoken 0.13.0
tilelang 0.1.9
tokenizers 0.22.2
tokenspeed-mla 0.1.2
tokenspeed-triton 3.7.10.post20260531
tomlkit 0.13.3
torch 2.11.0
torch_c_dlpack_ext 0.1.5
torchvision 0.26.0
tqdm 4.68.2
transformers 5.12.0
transformers-stream-generator 0.0.5
triton 3.6.0
trl 0.29.1
typer 0.25.1
typer-slim 0.24.0
typing_extensions 4.15.0
typing-inspection 0.4.2
tzdata 2026.2
urllib3 2.7.0
uvicorn 0.49.0
uvloop 0.22.1
vllm 0.23.0
watchfiles 1.2.0
websockets 15.0.1
Werkzeug 3.1.8
wheel 0.46.3
xgrammar 0.2.2
xxhash 3.7.0
yarl 1.24.2
z3-solver 4.15.4.0
zipp 4.1.0
zstandard 0.25.0

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

No repository file, test, or entry point is identified. Start by reproducing the causal_conv1d installation failure in the listed Python environment and capture the complete error output; done means the dependency installs and the Qwen3.5 9B GRPO GSM8K setup can proceed.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Active
Clarity
Needs clarification
Newbie friendliness
35/100

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