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When I tested the accuracy of the model, I encountered the following problem:
My test command is as follows:
export CUDA_VISIBLE_DEVICES=0,1,2,3 export NCCL_P2P_DISABLE=1 export NCCL_IB_DISABLE=1 export HF_ENDPOINT="https://hf-mirror.com" lm_eval --model hf --model_args pretrained=/data/models/arcee-ai/Qwen2___5-32B-Instruct-FP8,parallelize=True --tasks ceval-valid_accountant
My test machine is 8x4090x24GiB.
The piplist version is as follows:
Package Version --------------------------------- ------------- absl-py 2.1.0 accelerate 1.4.0 aiohappyeyeballs 2.4.6 aiohttp 3.11.12 aiohttp-cors 0.7.0 aiosignal 1.3.2 airportsdata 20241001 annotated-types 0.7.0 anthropic 0.45.2 anyio 4.8.0 argcomplete 3.5.3 astor 0.8.1 asttokens 3.0.0 async-timeout 5.0.1 attrs 25.1.0 auto_gptq 0.7.1 black 25.1.0 blake3 1.0.4 blinker 1.4 cachetools 5.5.1 certifi 2025.1.31 chardet 5.2.0 charset-normalizer 3.4.1 click 8.1.8 cloudpickle 3.1.1 colorama 0.4.6 colorful 0.5.6 compressed-tensors 0.9.1 cryptography 3.4.8 cuda-bindings 12.8.0 cuda-python 12.8.0 datamodel-code-generator 0.27.3 DataProperty 1.1.0 datasets 3.3.2 dbus-python 1.2.18 decorator 5.1.1 decord 0.6.0 depyf 0.18.0 dill 0.3.8 diskcache 5.6.3 distlib 0.3.9 distro 1.7.0 distro-info 1.1+ubuntu0.2 einops 0.8.1 evaluate 0.4.3 exceptiongroup 1.2.2 executing 2.2.0 fastapi 0.115.8 filelock 3.17.0 flashinfer-python 0.2.2.post1 frozenlist 1.5.0 fsspec 2024.6.1 gekko 1.2.1 genson 1.3.0 gguf 0.10.0 google-api-core 2.24.1 google-auth 2.38.0 googleapis-common-protos 1.67.0 grpcio 1.70.0 h11 0.14.0 hf_transfer 0.1.9 html5lib 1.1 httpcore 1.0.7 httplib2 0.20.2 httptools 0.6.4 httpx 0.28.1 huggingface-hub 0.28.1 idna 3.10 importlib_metadata 8.6.1 inflect 5.6.2 iniconfig 2.0.0 interegular 0.3.3 ipython 8.32.0 isort 6.0.0 jedi 0.19.2 jeepney 0.7.1 Jinja2 3.1.5 jiter 0.8.2 joblib 1.4.2 jsonlines 4.0.0 jsonschema 4.23.0 jsonschema-specifications 2024.10.1 keyring 23.5.0 lark 1.2.2 launchpadlib 1.10.16 lazr.restfulclient 0.14.4 lazr.uri 1.0.6 litellm 1.61.1 lm_eval 0.4.7 lm-format-enforcer 0.10.9 lxml 5.3.1 MarkupSafe 3.0.2 matplotlib-inline 0.1.7 mbstrdecoder 1.1.4 mistral_common 1.5.3 modelscope 1.22.3 more-itertools 8.10.0 mpmath 1.3.0 msgpack 1.1.0 msgspec 0.19.0 multidict 6.1.0 multiprocess 0.70.16 mypy-extensions 1.0.0 nest-asyncio 1.6.0 networkx 3.3 ninja 1.11.1.3 nltk 3.9.1 numexpr 2.10.2 numpy 1.26.4 nvidia-cublas-cu12 12.4.5.8 nvidia-cuda-cupti-cu12 12.4.127 nvidia-cuda-nvrtc-cu12 12.4.127 nvidia-cuda-runtime-cu12 12.4.127 nvidia-cudnn-cu12 9.1.0.70 nvidia-cufft-cu12 11.2.1.3 nvidia-curand-cu12 10.3.5.147 nvidia-cusolver-cu12 11.6.1.9 nvidia-cusparse-cu12 12.3.1.170 nvidia-cusparselt-cu12 0.6.2 nvidia-ml-py 12.570.86 nvidia-nccl-cu12 2.21.5 nvidia-nvjitlink-cu12 12.4.127 nvidia-nvtx-cu12 12.4.127 oauthlib 3.2.0 openai 1.62.0 opencensus 0.11.4 opencensus-context 0.1.3 opencv-python-headless 4.11.0.86 optimum 1.24.0 orjson 3.10.15 outlines 0.1.11 outlines_core 0.1.26 packaging 24.2 pandas 2.2.3 parso 0.8.4 partial-json-parser 0.2.1.1.post5 pathspec 0.12.1 pathvalidate 3.2.3 peft 0.14.0 pexpect 4.9.0 pillow 11.1.0 pip 25.0.1 platformdirs 4.3.6 pluggy 1.5.0 portalocker 3.1.1 prometheus_client 0.21.1 prometheus-fastapi-instrumentator 7.0.2 prompt_toolkit 3.0.50 propcache 0.2.1 proto-plus 1.26.0 protobuf 5.29.3 psutil 6.1.1 ptyprocess 0.7.0 pure_eval 0.2.3 py-cpuinfo 9.0.0 py-spy 0.4.0 pyarrow 19.0.1 pyasn1 0.6.1 pyasn1_modules 0.4.1 pybind11 2.13.6 pycountry 24.6.1 pydantic 2.10.6 pydantic_core 2.27.2 Pygments 2.19.1 PyGObject 3.42.1 PyJWT 2.3.0 pyparsing 2.4.7 pytablewriter 1.2.1 pytest 8.3.4 python-apt 2.4.0+ubuntu4 python-dateutil 2.9.0.post0 python-dotenv 1.0.1 python-multipart 0.0.20 pytz 2025.1 PyYAML 6.0.2 pyzmq 26.2.1 ray 2.42.1 referencing 0.36.2 regex 2024.11.6 requests 2.32.3 rouge 1.0.1 rouge_score 0.1.2 rpds-py 0.22.3 rsa 4.9 sacrebleu 2.5.1 safetensors 0.5.2 scikit-learn 1.6.1 scipy 1.15.2 SecretStorage 3.3.1 sentencepiece 0.2.0 setproctitle 1.3.4 setuptools 75.8.0 sgl-kernel 0.0.3.post sglang 0.4.3 six 1.17.0 smart-open 7.1.0 sniffio 1.3.1 sqlitedict 2.1.0 stack-data 0.6.3 starlette 0.45.3 sympy 1.13.1 tabledata 1.3.4 tabulate 0.9.0 tcolorpy 0.1.7 tenacity 9.0.0 threadpoolctl 3.5.0 tiktoken 0.8.0 tokenizers 0.21.0 tomli 2.2.1 torch 2.5.1 torchao 0.8.0 torchaudio 2.5.1 torchvision 0.20.1 tqdm 4.67.1 tqdm-multiprocess 0.0.11 traitlets 5.14.3 transformers 4.48.3 triton 3.1.0 typepy 1.3.4 typing_extensions 4.12.2 tzdata 2025.1 unattended-upgrades 0.1 urllib3 2.3.0 uvicorn 0.34.0 uvloop 0.21.0 virtualenv 20.29.2 vllm 0.7.2 wadllib 1.3.6 watchfiles 1.0.4 wcwidth 0.2.13 webencodings 0.5.1 websockets 14.2 wheel 0.45.1 word2number 1.1 wrapt 1.17.2 xformers 0.0.28.post3 xgrammar 0.1.11 xxhash 3.5.0 yarl 1.18.3 zipp 3.21.0 zstandard 0.23.0
I used the same method to test Qwen/Qwen2.5-32B-Instruct-GPTQ-Int4 and it was normal!
The text was updated successfully, but these errors were encountered:
Hi! HF datasets was experiencing some issues last couple of days. I think it should work if you try again.
Sorry, something went wrong.
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When I tested the accuracy of the model, I encountered the following problem:
My test command is as follows:
My test machine is 8x4090x24GiB.
The piplist version is as follows:
I used the same method to test Qwen/Qwen2.5-32B-Instruct-GPTQ-Int4 and it was normal!
The text was updated successfully, but these errors were encountered: