Repository: modelscope/evalscope
Issue: 第一个示例运行报错-Qwen2.5-0.5B-Instruct- gsm8k arc
Root cause: Configuration Error

## 问题描述 / Issue Description

请简要描述您遇到的问题。 / Please briefly describe the issue you encountered.
pip安装后跑默认示例脚本报错

## 使用的工具 / Tools Used
- [x] Native / 原生框架
- [ ] Opencompass backend
- [ ] VLMEvalKit backend
- [ ] RAGEval backend
- [ ] Perf / 模型推理压测工具
- [ ] Arena  /竞技场模式


## 执行的代码或指令 / Code or Commands Executed


请提供您执行的主要代码或指令。 / Please provide the main code or commands you executed. 例如 / For example:


```bash
# 例如：在终端中执行的指令 / Terminal command executed
pip install "evalscope[all]"
pip install "evalscope[app]"

evalscope eval \
 --model Qwen/Qwen2.5-0.5B-Instruct \
 --datasets gsm8k arc \
 --limit 5
```

## 错误日志 / Error Log

请粘贴完整的错误日志或控制台输出。 / Please paste the full error log or console output. 例如 / For example:

```
/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/onnxscript/converter.py:820: FutureWarning: 'onnxscript.values.Op.param_schemas' is deprecated in version 0.1 and will be removed in the future. Please use '.op_signature' instead.
  param_schemas = callee.param_schemas()
/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/onnxscript/converter.py:820: FutureWarning: 'onnxscript.values.OnnxFunction.param_schemas' is deprecated in version 0.1 and will be removed in the future. Please use '.op_signature' instead.
  param_schemas = callee.param_schemas()
2025-02-27 13:34:18.532361: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-02-27 13:34:18.539335: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:477] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1740634458.547678 1623989 cuda_dnn.cc:8310] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1740634458.550222 1623989 cuda_blas.cc:1418] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2025-02-27 13:34:18.558806: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2025-02-27 13:34:20,263 - evalscope - INFO - Args: Task config is provided with CommandLine type.
2025-02-27 13:34:20,596 - modelscope - WARNING - Using branch: master as version is unstable, use with caution
2025-02-27 13:34:20,859 - modelscope - INFO - Target directory already exists, skipping creation.
2025-02-27 13:34:21,312 - modelscope - WARNING - Using branch: master as version is unstable, use with caution
2025-02-27 13:34:21,744 - modelscope - INFO - Target directory already exists, skipping creation.
2025-02-27 13:34:21,823 - accelerate.utils.modeling - INFO - We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk).
2025-02-27 13:34:21,830 - accelerate.utils.modeling - INFO - Based on the current allocation process, no modules could be assigned to the following devices due to insufficient memory:
  - 0: 302094144 bytes required
These minimum requirements are specific to this allocation attempt and may vary. Consider increasing the available memory for these devices to at least the specified minimum, or adjusting the model config.
2025-02-27 13:34:22,406 - modelscope - WARNING - Using branch: master as version is unstable, use with caution
2025-02-27 13:34:22,801 - modelscope - INFO - Target directory already exists, skipping creation.
2025-02-27 13:34:22,803 - evalscope - INFO - Updating generation config ...
2025-02-27 13:34:22,804 - evalscope - INFO - Dump task config to ./outputs/20250227_133420/configs/task_config_035aac.yaml
2025-02-27 13:34:22,806 - evalscope - INFO - {
    "model": "Qwen/Qwen2.5-0.5B-Instruct",
    "model_id": "Qwen2.5-0.5B-Instruct",
    "model_args": {
        "revision": "master",
        "precision": "torch.float16",
        "device": "auto"
    },
    "template_type": null,
    "chat_template": null,
    "datasets": [
        "gsm8k",
        "arc"
    ],
    "dataset_args": {
        "gsm8k": {
            "name": "gsm8k",
            "dataset_id": "modelscope/gsm8k",
            "subset_list": [
                "main"
            ],
            "few_shot_num": 4,
            "few_shot_random": false,
            "train_split": "train",
            "eval_split": "test",
            "prompt_template": ""
        },
        "arc": {
            "name": "arc",
            "dataset_id": "modelscope/ai2_arc",
            "subset_list": [
                "ARC-Easy",
                "ARC-Challenge"
            ],
            "few_shot_num": 0,
            "few_shot_random": false,
            "train_split": "train",
            "eval_split": "test",
            "prompt_template": ""
        }
    },
    "dataset_dir": "/home/ws/.cache/modelscope/datasets",
    "dataset_hub": "modelscope",
    "generation_config": {
        "max_length": 2048,
        "max_new_tokens": 512,
        "do_sample": false,
        "top_k": 50,
        "top_p": 1.0,
        "temperature": 1.0
    },
    "eval_type": "checkpoint",
    "eval_backend": "Native",
    "eval_config": null,
    "stage": "all",
    "limit": 5,
    "mem_cache": false,
    "use_cache": null,
    "work_dir": "./outputs/20250227_133420",
    "outputs": null,
    "debug": false,
    "dry_run": false,
    "seed": 42,
    "api_url": null,
    "api_key": "EMPTY"
}
2025-02-27 13:34:22,807 - evalscope - INFO - **** Start evaluating on dataset modelscope/gsm8k ****
2025-02-27 13:34:22,807 - evalscope - INFO - Loading dataset from modelscope: > dataset_name: modelscope/gsm8k > subsets: ['main']
2025-02-27 13:34:27,734 - evalscope - INFO - Use default settings: > few_shot_num: 4, > few_shot_split: train, > target_eval_split: test
Downloading Model to directory: /home/ws/.cache/modelscope/hub/Qwen/Qwen2.5-0.5B-Instruct
Downloading Model to directory: /home/ws/.cache/modelscope/hub/Qwen/Qwen2.5-0.5B-Instruct
Downloading Model to directory: /home/ws/.cache/modelscope/hub/Qwen/Qwen2.5-0.5B-Instruct

Predicting(main):   0%|          | 0/5 [00:00<?, ?it/s]/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/transformers/generation/utils.py:2134: UserWarning: You are calling .generate() with the `input_ids` being on a device type different than your model's device. `input_ids` is on cuda, whereas the model is on cpu. You may experience unexpected behaviors or slower generation. Please make sure that you have put `input_ids` to the correct device by calling for example input_ids = input_ids.to('cpu') before running `.generate()`.
  warnings.warn(

Predicting(main):   0%|          | 0/5 [00:00<?, ?it/s]
Traceback (most recent call last):
  File "/home/ws/miniforge3/envs/py39/bin/evalscope", line 8, in <module>
    sys.exit(run_cmd())
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/evalscope/cli/cli.py", line 23, in run_cmd
    cmd.execute()
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/evalscope/cli/start_eval.py", line 31, in execute
    run_task(self.args)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/evalscope/run.py", line 32, in run_task
    return run_single_task(task_cfg, run_time)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/evalscope/run.py", line 45, in run_single_task
    return evaluate_model(task_cfg, outputs)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/evalscope/run.py", line 114, in evaluate_model
    res_dict = evaluator.eval(infer_cfg=task_cfg.generation_config, debug=task_cfg.debug, limit=task_cfg.limit)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/evalscope/evaluator/evaluator.py", line 344, in eval
    answers_list: list = self.get_answers(
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/evalscope/evaluator/evaluator.py", line 147, in get_answers
    answer_d: dict = self.model_adapter.predict(inputs=input_prompt, infer_cfg=infer_cfg)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/evalscope/models/chat_adapter.py", line 127, in predict
    response = self._model_generate(query, system_prompt, infer_cfg)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/evalscope/models/chat_adapter.py", line 99, in _model_generate
    output_ids = self.model.generate(**inputs, generation_config=self.generation_config)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/transformers/generation/utils.py", line 2252, in generate
    result = self._sample(
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/transformers/generation/utils.py", line 3251, in _sample
    outputs = self(**model_inputs, return_dict=True)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/transformers/models/qwen2/modeling_qwen2.py", line 1165, in forward
    outputs = self.model(
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/transformers/models/qwen2/modeling_qwen2.py", line 854, in forward
    inputs_embeds = self.embed_tokens(input_ids)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/torch/nn/modules/sparse.py", line 163, in forward
    return F.embedding(
  File "/home/ws/miniforge3/envs/py39/lib/python3.9/site-packages/torch/nn/functional.py", line 2264, in embedding
    return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0! (when checking argument for argument index in method wrapper_CUDA__index_select)


```

## 运行环境 / Runtime Environment

- 操作系统 / Operating System:
  - [ ] Windows
  - [ ] macOS
  - [x] Ubuntu

- Python版本 / Python Version:
  - [ ] 3.11
  - [ ] 3.10
  - [x] 3.9


## 其他信息 / Additional Information

如果有其他相关信息，请在此处提供。 / If there is any other relevant information, please provide it here.
`pip freeze` result:
```plain
absl-py==2.1.0
accelerate==1.3.0
adabound==0.0.5
addict==2.4.0
aiofiles==23.2.1
aiohttp==3.9.5
aiosignal==1.3.1
alabaster==0.7.16
albumentations==1.3.1
aliyun-log-python-sdk==0.9.11
aliyun-python-sdk-core==2.15.1
aliyun-python-sdk-kms==2.16.3
altair==5.3.0
altgraph==0.17.4
AMFM_decompy==1.0.11
analytics-python==1.4.post1
annotated-types==0.6.0
antlr4-python3-runtime==4.9.3
anyio==4.3.0
appdirs==1.4.4
asttokens==2.4.1
astunparse==1.6.3
async-timeout==4.0.3
attrdict==2.0.1
attrs==23.2.0
audiomentations==0.34.1
audioread==3.0.1
av==12.0.0
Babel==2.15.0
backoff==1.10.0
bcrypt==4.2.0
beartype==0.18.5
beautifulsoup4==4.12.3
bibtexparser==2.0.0b7
binpacking==1.5.2
bitarray==2.9.2
bitsandbytes==0.45.3
black==24.10.0
blinker==1.8.2
boto3==1.7.84
botocore==1.36.20
braceexpand==0.1.7
build==1.2.1
cached_path==1.6.7
cachetools==5.3.3
certifi==2024.2.2
cffi==1.16.0
cfgv==3.4.0
char-featurizer==1.0.0
chardet==5.2.0
charset-normalizer==3.3.2
-e git+https://github.com/2noise/ChatTTS.git@b978e88ce2f1a5c9bb565f744d8d282f05504f9e#egg=ChatTTS
chumpy==0.70
click==8.1.7
clldutils==3.22.2
cmudict==1.0.23
cn2an==0.5.22
colorama==0.4.6
coloredlogs==15.0.1
colorlog==6.8.2
compress-pickle==2.1.0
conan==2.3.2
configparser==7.0.0
conformer==0.3.2
contourpy==1.2.1
cpm-kernels==1.0.11
crcmod==1.7
cryptography==42.0.7
csvw==3.3.0
ctranslate2==4.2.1
cycler==0.12.1
Cython @ file:///home/conda/feedstock_root/build_artifacts/cython_1652809236105/work
dacite==1.8.1
dataclasses-json==0.6.7
DataProperty==1.0.1
datasets==3.0.1
dateparser==1.2.0
decorator==4.4.2
decord==0.6.0
DeepFilterLib==0.5.6
DeepFilterNet==0.5.6
deepspeech-gpu==0.9.3
Deprecated==1.2.14
diffusers==0.27.2
dill==0.3.6
diskcache==5.6.3
Distance==0.1.3
distlib==0.3.8
distro==1.8.0
dlinfo==1.2.1
dnspython==2.6.1
docker-pycreds==0.4.0
docopt==0.6.2
docstring_parser==0.16
docutils==0.21.2
dominate==2.9.1
dtw-python==1.4.2
easydict==1.13
editdistance==0.8.1
einops==0.8.0
einx==0.3.0
elastic-transport==8.15.0
elasticsearch==8.15.1
ema-pytorch==0.7.7
email_validator==2.1.1
encodec==0.1.1
eng_to_ipa==0.0.2
et_xmlfile==2.0.0
eval_type_backport==0.2.2
evalscope==0.9.0
evaluate==0.4.3
exceptiongroup==1.2.1
executing==2.0.1
face-alignment==1.4.1
facenet-pytorch==2.5.3
facexlib==0.3.0
fairseq==0.12.2
faiss-cpu==1.8.0
fastapi==0.112.2
fastapi-cli==0.0.3
fasteners==0.19
faster-whisper==1.0.2
ffmpeg-python==0.2.0
ffmpy==0.3.1
filelock==3.14.0
filterpy==1.4.5
fire==0.7.0
-e git+https://github.com/fishaudio/fish-speech@74c3cb38e47ae9a99a91e24eefd4284093643924#egg=fish_speech
FLAME_PyTorch==0.0.1
Flask==3.0.3
flatbuffers==24.3.25
fonttools==4.51.0
freetype-py==2.4.0
frozendict==2.4.4
frozenlist==1.4.1
fsspec==2024.2.0
fugashi==1.3.2
funasr==1.1.14
func_timeout==4.3.5
future==1.0.0
fuzzywuzzy==0.18.0
fvcore==0.1.5.post20221221
g2p-en==2.1.0
gast==0.5.4
gdown==5.2.0
gekko==1.1.3
ghp-import==2.1.0
gitdb==4.0.11
GitPython==3.1.43
google-api-core==2.24.1
google-auth==2.38.0
google-cloud-core==2.4.1
google-cloud-storage==2.19.0
google-crc32c==1.6.0
google-pasta==0.2.0
google-resumable-media==2.7.2
googleapis-common-protos==1.67.0
gpt4all==2.8.2
GPUtil==1.4.0
gradio==4.44.1
gradio_client==1.3.0
greenlet==3.1.1
griffe==0.45.2
grpcio==1.63.0
h11==0.14.0
h5py==3.12.1
hdbscan @ file:///home/conda/feedstock_root/build_artifacts/hdbscan_1720077390893/work
hickle==5.0.3
httpcore==1.0.5
httptools==0.6.1
httpx==0.27.0
httpx-sse==0.4.0
huggingface-hub==0.25.2
human-eval==1.0.3
humanfriendly==10.0
hydra-core==1.3.2
HyperPyYAML==1.2.2
identify==2.6.0
idna==3.7
imageio==2.34.1
imageio-ffmpeg==0.4.9
imagesize==1.4.1
imgaug==0.4.0
immutabledict==4.2.1
importlib_metadata==7.1.0
importlib_resources==6.4.0
inflect==7.2.1
iopath==0.1.10
ipython==8.18.1
isodate==0.6.1
itsdangerous==2.2.0
jaconv==0.3.4
jamo==0.4.1
jax==0.4.28
jaxlib==0.4.28
jedi==0.19.1
jieba==0.42.1
Jinja2==3.1.3
jiter==0.8.2
jiwer==3.0.4
jmespath==0.10.0
joblib @ file:///home/conda/feedstock_root/build_artifacts/joblib_1714665484399/work
json5==0.9.25
jsonargparse==4.32.1
jsonlines==4.0.0
jsonpatch==1.33
jsonpointer==3.0.0
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
julius==0.2.7
kaldiio==2.18.0
keras==3.8.0
Keras-Preprocessing==1.1.2
kiwisolver==1.4.5
kornia==0.7.2
kornia_rs==0.1.3
langchain==0.3.19
langchain-community==0.3.18
langchain-core==0.3.40
langchain-openai==0.3.7
langchain-text-splitters==0.3.6
langid==1.1.6
langsmith==0.3.11
language-tags==1.2.0
lazy_loader==0.4
Levenshtein==0.26.1
libclang==18.1.1
librosa==0.9.2
lightning==2.3.0.dev20240428
lightning-bolts==0.5.0
lightning-utilities==0.11.2
linkify-it-py==2.0.3
litdata==0.2.17
litserve==0.2.2
llvmlite==0.42.0
lm_eval==0.4.4
lmdb==1.4.1
local-attention==1.9.1
loguru==0.7.2
lxml==5.2.2
Markdown==3.6
markdown-it-py==2.2.0
MarkupSafe==2.1.5
marshmallow==3.26.1
matplotlib==3.8.4
matplotlib-inline==0.1.7
mbstrdecoder==1.1.3
mdit-py-plugins==0.3.3
mdurl==0.1.2
mecab-python3==1.0.9
mediapipe==0.10.11
memory-profiler==0.61.0
mergedeep==1.3.4
mkdocs==1.6.0
mkdocs-autorefs==1.0.1
mkdocs-get-deps==0.2.0
mkdocs-material==9.5.25
mkdocs-material-extensions==1.3.1
mkdocstrings==0.25.1
mkdocstrings-python==1.10.3
ml-dtypes==0.4.1
mlx==0.18.0
mmcv==2.1.0
mmengine==0.10.4
mmengine-lite==0.10.6
MNN_Internal==3.0.5
modelscope==1.20.1
monotonic==1.6
more-itertools==10.2.0
moviepy==1.0.3
mpmath==1.3.0
ms-opencompass==0.1.6
ms-vlmeval==0.0.13
mteb==1.19.4
multidict==6.0.5
multiprocess==0.70.14
munch==4.0.0
mypy-extensions==1.0.0
namex==0.0.8
natsort==8.4.0
nest-asyncio==1.6.0
networkx==3.2.1
nltk==3.9.1
nodeenv==1.9.1
num2words==0.5.13
numba==0.59.1
numexpr==2.10.1
numpy==1.26.4
nvidia-cublas-cu11==11.10.3.66
nvidia-cublas-cu12==12.1.3.1
nvidia-cuda-cupti-cu12==12.1.105
nvidia-cuda-nvrtc-cu11==11.7.99
nvidia-cuda-nvrtc-cu12==12.1.105
nvidia-cuda-runtime-cu11==11.7.99
nvidia-cuda-runtime-cu12==12.1.105
nvidia-cudnn-cu11==8.5.0.96
nvidia-cudnn-cu12==8.9.2.26
nvidia-cufft-cu12==11.0.2.54
nvidia-curand-cu12==10.3.2.106
nvidia-cusolver-cu12==11.4.5.107
nvidia-cusparse-cu12==12.1.0.106
nvidia-nccl-cu12==2.20.5
nvidia-nvjitlink-cu12==12.4.127
nvidia-nvtx-cu12==12.1.105
omegaconf==2.3.0
onnx==1.17.0
onnxruntime==1.19.2
onnxruntime-gpu==1.19.2
onnxscript==0.1.0.dev20250106
onnxsim==0.4.36
openai==1.64.0
openai-whisper==20231117
OpenCC==1.1.9
opencv-contrib-python==4.9.0.80
opencv-python==4.8.1.78
opencv-python-headless==4.9.0.80
openi==1.3.0
openpyxl==3.1.5
opt-einsum==3.3.0
optree==0.11.0
orjson==3.10.3
oss2==2.18.5
packaging==24.2
paginate==0.5.6
pandas==2.2.2
paramiko==3.5.0
parso==0.8.4
patch-ng==1.17.4
pathspec==0.12.1
pathtools==0.1.2
pathvalidate==3.2.1
peft==0.12.0
pexpect==4.9.0
phonemizer==3.2.1
pillow==10.3.0
platformdirs==4.2.2
plotly==5.22.0
ply==3.11
polars==1.23.0
pooch==1.8.1
portalocker==2.8.2
praat-parselmouth==0.4.3
pre-commit==3.7.1
prettytable==3.10.0
primePy==1.3
proces==0.1.7
proglog==0.1.10
progressbar==2.5
prompt_toolkit==3.0.45
proto-plus==1.26.0
protobuf==3.20.3
psutil==5.9.8
ptyprocess==0.7.0
pure-eval==0.2.2
pyarrow==16.1.0
pyasn1==0.6.0
pyasn1_modules==0.4.0
pybind11==2.13.6
pycparser==2.22
pycryptodome==3.20.0
pydantic==2.8.2
pydantic-settings==2.8.0
pydantic_core==2.20.1
pydeck==0.9.1
pyDeprecate==0.3.1
pydub==0.25.1
pyglet==2.0.15
Pygments==2.18.0
pyinstaller==6.10.0
pyinstaller-hooks-contrib==2024.8
pykakasi==2.2.1
pylatexenc==2.10
pymdown-extensions==10.8.1
Pympler==1.1
PyNaCl==1.5.0
pynndescent==0.5.12
pynvml==11.5.3
PyOpenGL==3.1.0
pyparsing==3.1.2
pypinyin==0.51.0
pyproject_hooks==1.1.0
pyrender==0.1.39
pysbd==0.3.4
PySocks==1.7.1
pytablewriter==1.2.0
python-dateutil==2.9.0.post0
python-dotenv==1.0.1
python-Levenshtein==0.26.1
python-multipart==0.0.9
python_speech_features==0.6
pytorch-lightning==2.4.0
pytorch-wpe==0.0.1
pytrec-eval-terrier==0.5.6
pytz==2024.1
pyworld==0.3.2
PyYAML==6.0.1
pyyaml_env_tag==0.1
pyzmq==26.0.3
qudida==0.0.4
ragas==0.2.9
rank-bm25==0.2.2
RapidFuzz==3.10.1
rdflib==7.0.0
referencing==0.35.1
regex==2024.5.10
requests==2.32.3
requests-toolbelt==1.0.0
resampy==0.4.2
rfc3986==1.5.0
rich==13.7.1
rotary-embedding-torch==0.6.2
rouge==1.0.1
rouge-chinese==1.0.3
rouge_score==0.1.2
rpds-py==0.18.1
rsa==4.9
ruamel.yaml==0.18.6
ruamel.yaml.clib==0.2.12
ruff==0.4.4
s3transfer==0.1.13
sacrebleu==2.4.2
safetensors==0.4.3
scenedetect==0.6.4
scikit-image==0.22.0
scikit-learn==1.3.2
scikit-sound==0.2.14
scikit-video==1.1.11
scipy==1.10.1
seaborn==0.13.2
segments==2.2.1
semantic-version==2.10.0
sentence-transformers==3.4.1
sentencepiece==0.2.0
sentry-sdk==2.1.1
setproctitle==1.3.3
shapely==2.0.4
shellingham==1.5.4
shtab==1.7.1
simple-ddl-parser==1.7.1
simplejson==3.19.2
six @ file:///home/conda/feedstock_root/build_artifacts/six_1620240208055/work
smmap==5.0.1
smplx==0.1.28
snac==1.2.1
sniffio==1.3.1
sortedcontainers==2.4.0
sounddevice==0.4.6
soundfile==0.12.1
soupsieve==2.5
soxr==0.3.7
speechbrain==1.0.2
SQLAlchemy==2.0.38
sqlitedict==2.1.0
sse-starlette==2.1.3
stack-data==0.6.3
starlette==0.38.2
streamlit==1.34.0
sty==1.0.6
subprocess32==3.5.4
sympy==1.13.1
tabledata==1.3.3
tabulate==0.9.0
tcolorpy==0.1.6
tenacity==8.3.0
tensorboard==2.18.0
tensorboard-data-server==0.7.2
tensorflow==2.18.0
tensorflow-io-gcs-filesystem==0.37.0
termcolor==2.3.0
tf_keras==2.18.0
threadpoolctl @ file:///home/conda/feedstock_root/build_artifacts/threadpoolctl_1714400101435/work
tifffile==2024.5.10
tiktoken==0.7.0
timeout-decorator==0.5.0
timm==0.9.16
tokenizers==0.21.0
toml==0.10.2
tomli==2.0.1
tomlkit==0.12.0
toolz==0.12.1
torch==2.3.1+cu121
torch-audiomentations==0.11.0
torch-complex==0.4.3
torch-pitch-shift==1.2.4
torchaudio==2.3.1+cu121
torchcrepe==0.0.20
torchdiffeq==0.2.5
torchfcpe==0.0.4
torchfile==0.1.0
torchgeometry==0.1.2
torchlibrosa==0.1.0
torchmetrics==1.4.0.post0
torchvision==0.18.1+cu121
tornado==6.4
tqdm==4.66.5
tqdm-multiprocess==0.0.11
traitlets==5.14.3
transformers==4.47.1
transformers-stream-generator==0.0.5
trimesh==3.6.18
triton==2.3.1
trl==0.11.4
typeguard==4.2.1
typepy==1.3.2
typer==0.12.3
typeshed_client==2.7.0
typing-inspect==0.9.0
typing_extensions==4.11.0
tyro==0.9.11
tzdata==2024.1
tzlocal==5.2
uc-micro-py==1.0.3
ujson==5.10.0
umap==0.1.1
umap-learn==0.5.6
unicorn==2.1.2
Unidecode==1.3.8
unidic-lite==1.0.8
uritemplate==4.1.1
urllib3==2.3.0
uv==0.6.0
uvicorn==0.29.0
uvloop==0.19.0
validators==0.34.0
vector-quantize-pytorch==1.14.23
virtualenv==20.26.3
vocos==0.1.0
voicefixer==0.1.3
wandb==0.19.6
watchdog==4.0.0
watchfiles==0.21.0
wavmark==0.0.3
wcwidth==0.2.13
webdataset==0.2.100
websockets==11.0.3
Werkzeug==3.0.3
wget==3.2
whisper-timestamped==1.15.4
word2number==1.1
wrapt==1.16.0
x-transformers==2.0.2
XlsxWriter==3.2.2
xxhash==3.4.1
yacs==0.1.8
yapf==0.40.2
yarl==1.9.4
yaspin==3.1.0
zhconv==1.4.3
zipp==3.18.1
zstandard==0.23.0

```

请问你使用的显卡是什么，显存是否足够

> 请问你使用的显卡是什么，显存是否足够

是4070 Ti，显卡12G，我增加`--model-args device_map=cuda` 选项就可以了，可以看看是不是默认选项没有设置对

默认的device map是auto，可能有些权重被分到cpu上了

> 感谢你的反馈！我们将关闭此问题。如果您有任何疑问，请随时重新打开它。如果EvalScope对您有所帮助，欢迎给我们点个STAR以示支持，谢谢！