Llava在重新读取预处理器的时候报错 #177
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额，你这个llavanext吧？和llava是不一样的。（我不确定奥） |
llava 和llavanext我都试啦，这个其实就是llava1.5和llava1.6, 1.6主要就是预处理的图像size不太一样。原版的llava我也试了，也是一样的错误才去试llavanext的 |
请问您的transformers版本是多少哇，是不是这个的原因，我直接down下来notebook来运行qwen4b 一行一行执行也会报同样的错误，感觉是环境的问题。 |
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看了一下，可能是transformers版本不一样，我这里是 absl-py==2.0.0
accelerate==0.30.1
addict==2.4.0
aiofiles==23.2.1
aiohttp==3.8.6
aiohttp-cors==0.7.0
aioprometheus==23.12.0
aiorwlock==1.4.0
aiosignal==1.3.1
aliyun-python-sdk-core==2.14.0
aliyun-python-sdk-kms==2.16.2
altair==5.1.2
amqp==5.2.0
annotated-types==0.6.0
anyio==3.7.1
argon2-cffi==23.1.0
argon2-cffi-bindings==21.2.0
arrow==1.3.0
asttokens==2.4.1
async-lru==2.0.4
async-timeout==4.0.3
attrs==23.1.0
Babel==2.13.1
beautifulsoup4==4.12.2
beir==2.0.0
billiard==4.2.0
bitsandbytes==0.42.0
bleach==6.1.0
blessed==1.20.0
blinker==1.7.0
Brotli @ file:///tmp/abs_ecyw11_7ze/croots/recipe/brotli-split_1659616059936/work
C-MTEB==1.1.1
cachetools==5.3.2
cchardet==2.1.7
celery==5.3.6
certifi @ file:///croot/certifi_1690232220950/work/certifi
cffi @ file:///croot/cffi_1670423208954/work
chardet==5.2.0
charset-normalizer @ file:///tmp/build/80754af9/charset-normalizer_1630003229654/work
click==8.1.7
click-didyoumean==0.3.0
click-plugins==1.1.1
click-repl==0.3.0
cloudpickle==3.0.0
colorama==0.4.6
coloredlogs==15.0.1
colorful==0.5.6
comm==0.1.4
contourpy==1.2.0
crcmod==1.7
cryptography @ file:///croot/cryptography_1694444244250/work
cupy-cuda12x==12.1.0
cycler==0.12.1
datasets==2.14.6
debugpy==1.8.1
decorator==5.1.1
deepspeed==0.14.0
defusedxml==0.7.1
dill==0.3.7
diskcache==5.6.3
distlib==0.3.8
distro==1.9.0
docopt==0.6.2
einops==0.7.0
elastic-transport==8.13.1
elasticsearch==7.9.1
elasticsearch-dsl==8.11.0
emoji==2.8.0
et-xmlfile==1.1.0
evaluate==0.4.1
exceptiongroup==1.1.3
executing==2.0.1
faiss-cpu==1.7.4
fastapi==0.104.1
fastjsonschema==2.18.1
fastrlock==0.8.2
ffmpy==0.3.2
filelock==3.13.1
Flask==3.0.0
flatbuffers==23.5.26
fonttools==4.47.2
fqdn==1.5.1
frozenlist==1.4.0
fsspec==2023.10.0
gast==0.5.4
gitdb==4.0.11
GitPython==3.1.40
gmpy2 @ file:///tmp/build/80754af9/gmpy2_1645455533097/work
google-api-core==2.16.1
google-auth==2.25.2
google-auth-oauthlib==1.2.0
googleapis-common-protos==1.62.0
gpustat==1.1.1
gradio==4.23.0
gradio_client==0.14.0
grpcio==1.60.0
h11==0.14.0
hjson==3.1.0
hnswlib==0.8.0
httpcore==1.0.1
httptools==0.6.1
httpx==0.25.1
huggingface-hub==0.23.2
humanfriendly==10.0
idna @ file:///croot/idna_1666125576474/work
importlib-metadata==6.8.0
importlib_resources==6.4.0
interegular==0.3.3
ipykernel==6.26.0
ipython==8.17.2
ipython-genutils==0.2.0
ipywidgets==8.1.1
isoduration==20.11.0
itsdangerous==2.1.2
jedi==0.19.1
jieba==0.42.1
Jinja2 @ file:///croot/jinja2_1666908132255/work
jmespath==0.10.0
joblib==1.3.2
json5==0.9.14
jsonlines==4.0.0
jsonpointer==2.4
jsonschema==4.19.2
jsonschema-specifications==2023.7.1
jupyter==1.0.0
jupyter-console==6.6.3
jupyter-events==0.8.0
jupyter-lsp==2.2.0
jupyter_client==8.5.0
jupyter_core==5.5.0
jupyter_server==2.9.1
jupyter_server_terminals==0.4.4
jupyterlab==4.0.7
jupyterlab-pygments==0.2.2
jupyterlab-widgets==3.0.9
jupyterlab_server==2.25.0
kiwisolver==1.4.5
kombu==5.3.4
lark==1.1.9
llvmlite==0.42.0
Markdown==3.5.1
markdown-it-py==3.0.0
MarkupSafe @ file:///opt/conda/conda-bld/markupsafe_1654597864307/work
matplotlib==3.8.2
matplotlib-inline==0.1.6
mdurl==0.1.2
mistune==3.0.2
mkl-fft @ file:///croot/mkl_fft_1695058164594/work
mkl-random @ file:///croot/mkl_random_1695059800811/work
mkl-service==2.4.0
modelscope==1.11.0
mpmath @ file:///croot/mpmath_1690848262763/work
msgpack==1.0.7
mteb==1.1.1
multidict==6.0.4
multiprocess==0.70.15
nbclient==0.8.0
nbconvert==7.10.0
nbformat==5.9.2
nest-asyncio==1.5.8
networkx @ file:///croot/networkx_1690561992265/work
ninja==1.11.1.1
nltk==3.8.1
notebook==7.0.6
notebook_shim==0.2.3
numba==0.59.1
numpy @ file:///croot/numpy_and_numpy_base_1695830428084/work/dist/numpy-1.26.0-cp310-cp310-linux_x86_64.whl#sha256=fc2732718bc9e06a7b702492cb4f5afffe9671083930452d894377bf563464a3
nvidia-cublas-cu11==11.11.3.6
nvidia-cublas-cu12==12.1.3.1
nvidia-cuda-cupti-cu11==11.8.87
nvidia-cuda-cupti-cu12==12.1.105
nvidia-cuda-nvrtc-cu11==11.8.89
nvidia-cuda-nvrtc-cu12==12.1.105
nvidia-cuda-runtime-cu11==11.8.89
nvidia-cuda-runtime-cu12==12.1.105
nvidia-cudnn-cu11==8.7.0.84
nvidia-cudnn-cu12==8.9.2.26
nvidia-cufft-cu11==10.9.0.58
nvidia-cufft-cu12==11.0.2.54
nvidia-curand-cu11==10.3.0.86
nvidia-curand-cu12==10.3.2.106
nvidia-cusolver-cu11==11.4.1.48
nvidia-cusolver-cu12==11.4.5.107
nvidia-cusparse-cu11==11.7.5.86
nvidia-cusparse-cu12==12.1.0.106
nvidia-ml-py==12.535.133
nvidia-nccl-cu11==2.19.3
nvidia-nccl-cu12==2.18.1
nvidia-nvjitlink-cu12==12.3.101
nvidia-nvtx-cu11==11.8.86
nvidia-nvtx-cu12==12.1.105
nvitop==1.3.1
oauthlib==3.2.2
onnx==1.15.0
onnxruntime==1.16.3
onnxruntime-gpu==1.16.3
openai==1.14.3
opencensus==0.11.4
opencensus-context==0.1.3
openpyxl==3.1.2
optimum==1.16.2
orjson==3.9.15
oss2==2.18.4
outlines==0.0.37
overrides==7.4.0
packaging==23.2
pandas==2.1.2
pandocfilters==1.5.0
parso==0.8.3
peft==0.9.0
pexpect==4.8.0
Pillow @ file:///croot/pillow_1696580024257/work
pipreqs==0.4.13
platformdirs==3.11.0
prometheus-client==0.18.0
prompt-toolkit==3.0.39
protobuf==4.23.4
psutil==5.9.6
ptyprocess==0.7.0
pure-eval==0.2.2
py-cpuinfo==9.0.0
py-spy==0.3.14
pyarrow==13.0.0
pyasn1==0.5.1
pyasn1-modules==0.3.0
pycparser @ file:///tmp/build/80754af9/pycparser_1636541352034/work
pycryptodome==3.20.0
pydantic==2.6.4
pydantic_core==2.16.3
pydeck==0.8.1b0
pydub==0.25.1
Pygments==2.16.1
PyJWT==2.8.0
pynvml==11.5.0
pyOpenSSL @ file:///croot/pyopenssl_1690223430423/work
pyparsing==3.1.1
PySocks @ file:///home/builder/ci_310/pysocks_1640793678128/work
python-dateutil==2.8.2
python-dotenv==1.0.1
python-json-logger==2.0.7
python-multipart==0.0.9
pytrec-eval==0.5
pytz==2023.3.post1
PyYAML @ file:///croot/pyyaml_1698096049011/work
pyzmq==25.1.1
qtconsole==5.4.4
QtPy==2.4.1
quantile-python==1.1
rank-bm25==0.2.2
ray==2.9.1
redis==5.0.1
referencing==0.30.2
regex==2023.10.3
replicate==0.17.0
requests @ file:///croot/requests_1690400202158/work
requests-oauthlib==1.3.1
responses==0.18.0
rfc3339-validator==0.1.4
rfc3986-validator==0.1.1
rich==13.6.0
rpds-py==0.10.6
rsa==4.9
ruff==0.3.4
safetensors==0.4.2
scikit-learn==1.3.2
scipy==1.11.3
semantic-version==2.10.0
Send2Trash==1.8.2
sentence-transformers==3.0.0
sentencepiece==0.1.99
shellingham==1.5.4
simplejson==3.19.2
six==1.16.0
smart-open==6.4.0
smmap==5.0.1
sniffio==1.3.0
sortedcontainers==2.4.0
soupsieve==2.5
sse-starlette==1.8.1
stack-data==0.6.3
starlette==0.27.0
streamlit==1.30.0
sympy @ file:///croot/sympy_1668202399572/work
tabulate==0.9.0
tenacity==8.2.3
tensorboard==2.16.2
tensorboard-data-server==0.7.2
tensorboardX==2.6.2.2
termcolor==2.3.0
terminado==0.17.1
threadpoolctl==3.2.0
tiktoken==0.5.2
timm==0.9.12
tinycss2==1.2.1
tokenizers==0.19.1
toml==0.10.2
tomli==2.0.1
tomlkit==0.12.0
toolz==0.12.0
torch==2.1.0
torchaudio==2.1.0
torchvision==0.16.0
tornado==6.3.3
tqdm==4.66.1
traitlets==5.13.0
transformers==4.41.1
transformers-stream-generator==0.0.4
triton==2.1.0
typer==0.9.4
types-python-dateutil==2.8.19.14
typing_extensions @ file:///croot/typing_extensions_1690297465030/work
tzdata==2023.3
tzlocal==5.2
uniem==0.3.3
uri-template==1.3.0
urllib3 @ file:///croot/urllib3_1698257533958/work
uvicorn==0.24.0.post1
uvloop==0.19.0
validators==0.22.0
vine==5.1.0
virtualenv==20.25.0
vllm==0.3.3
watchdog==3.0.0
watchfiles==0.21.0
wcwidth==0.2.9
webcolors==1.13
webencodings==0.5.1
websocket-client==1.6.4
websockets==11.0.3
Werkzeug==3.0.1
widgetsnbextension==4.0.9
xformers==0.0.23.post1
XlsxWriter==3.1.9
xxhash==3.4.1
yapf==0.40.2
yarg==0.1.9
yarl==1.9.2
zhipuai==2.0.1
zipp==3.17.0
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你好，老师，我升级到了4.41.2,然后已经可以了。因为我的环境是之前安装的，所以transformers版本有些滞后会有这个问题。 |
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在将模型保存下来后然后重新读取的时候，读取预处理器会报错。下边是错误内容，transformers版本为4.40.1， torch版本为2.0.1+cuda11.8, 设备为移动端RTX4080， 请问是tranformers版本的问题吗？那么我安装哪个版本呢？
{
"name": "TypeError",
"message": "not a string",
"stack": "---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Cell In[2], line 1
----> 1 llava_processor = LlavaNextProcessor.from_pretrained(
2 "LlavaNext1.6-Qwen1.5-0.5B-Chat/model001"
3 )
File c:\Users\zhiyuanUSYD\miniconda3\envs\autoGluon\lib\site-packages\transformers\processing_utils.py:465, in ProcessorMixin.from_pretrained(cls, pretrained_model_name_or_path, cache_dir, force_download, local_files_only, token, revision, **kwargs)
462 if token is not None:
463 kwargs["token"] = token
--> 465 args = cls._get_arguments_from_pretrained(pretrained_model_name_or_path, **kwargs)
466 processor_dict, kwargs = cls.get_processor_dict(pretrained_model_name_or_path, **kwargs)
468 return cls.from_args_and_dict(args, processor_dict, **kwargs)
File c:\Users\zhiyuanUSYD\miniconda3\envs\autoGluon\lib\site-packages\transformers\processing_utils.py:511, in ProcessorMixin._get_arguments_from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
508 else:
509 attribute_class = getattr(transformers_module, class_name)
--> 511 args.append(attribute_class.from_pretrained(pretrained_model_name_or_path, **kwargs))
512 return args
File c:\Users\zhiyuanUSYD\miniconda3\envs\autoGluon\lib\site-packages\transformers\tokenization_utils_base.py:2089, in PreTrainedTokenizerBase.from_pretrained(cls, pretrained_model_name_or_path, cache_dir, force_download, local_files_only, token, revision, trust_remote_code, *init_inputs, **kwargs)
2086 else:
2087 logger.info(f"loading file {file_path} from cache at {resolved_vocab_files[file_id]}")
-> 2089 return cls._from_pretrained(
2090 resolved_vocab_files,
2091 pretrained_model_name_or_path,
2092 init_configuration,
2093 *init_inputs,
2094 token=token,
2095 cache_dir=cache_dir,
2096 local_files_only=local_files_only,
2097 _commit_hash=commit_hash,
2098 _is_local=is_local,
2099 trust_remote_code=trust_remote_code,
2100 **kwargs,
2101 )
File c:\Users\zhiyuanUSYD\miniconda3\envs\autoGluon\lib\site-packages\transformers\tokenization_utils_base.py:2311, in PreTrainedTokenizerBase._from_pretrained(cls, resolved_vocab_files, pretrained_model_name_or_path, init_configuration, token, cache_dir, local_files_only, _commit_hash, _is_local, trust_remote_code, *init_inputs, **kwargs)
2309 # Instantiate the tokenizer.
2310 try:
-> 2311 tokenizer = cls(*init_inputs, **init_kwargs)
2312 except OSError:
2313 raise OSError(
2314 "Unable to load vocabulary from file. "
2315 "Please check that the provided vocabulary is accessible and not corrupted."
2316 )
File c:\Users\zhiyuanUSYD\miniconda3\envs\autoGluon\lib\site-packages\transformers\models\llama\tokenization_llama_fast.py:124, in LlamaTokenizerFast.init(self, vocab_file, tokenizer_file, clean_up_tokenization_spaces, unk_token, bos_token, eos_token, add_bos_token, add_eos_token, use_default_system_prompt, add_prefix_space, **kwargs)
119 logger.warning_once(
120 "You set
add_prefix_space. The tokenizer needs to be converted from the slow tokenizers"121 )
122 kwargs["from_slow"] = True
--> 124 super().init(
125 vocab_file=vocab_file,
126 tokenizer_file=tokenizer_file,
127 clean_up_tokenization_spaces=clean_up_tokenization_spaces,
128 unk_token=unk_token,
129 bos_token=bos_token,
130 eos_token=eos_token,
131 add_bos_token=add_bos_token,
132 add_eos_token=add_eos_token,
133 use_default_system_prompt=use_default_system_prompt,
134 **kwargs,
135 )
136 self._add_bos_token = add_bos_token
137 self._add_eos_token = add_eos_token
File c:\Users\zhiyuanUSYD\miniconda3\envs\autoGluon\lib\site-packages\transformers\tokenization_utils_fast.py:117, in PreTrainedTokenizerFast.init(self, *args, **kwargs)
114 fast_tokenizer = convert_slow_tokenizer(slow_tokenizer)
115 elif self.slow_tokenizer_class is not None:
116 # We need to create and convert a slow tokenizer to build the backend
--> 117 slow_tokenizer = self.slow_tokenizer_class(*args, **kwargs)
118 fast_tokenizer = convert_slow_tokenizer(slow_tokenizer)
119 else:
File c:\Users\zhiyuanUSYD\miniconda3\envs\autoGluon\lib\site-packages\transformers\models\llama\tokenization_llama.py:169, in LlamaTokenizer.init(self, vocab_file, unk_token, bos_token, eos_token, pad_token, sp_model_kwargs, add_bos_token, add_eos_token, clean_up_tokenization_spaces, use_default_system_prompt, spaces_between_special_tokens, legacy, add_prefix_space, **kwargs)
167 self.add_eos_token = add_eos_token
168 self.use_default_system_prompt = use_default_system_prompt
--> 169 self.sp_model = self.get_spm_processor(kwargs.pop("from_slow", False))
170 self.add_prefix_space = add_prefix_space
172 super().init(
173 bos_token=bos_token,
174 eos_token=eos_token,
(...)
185 **kwargs,
186 )
File c:\Users\zhiyuanUSYD\miniconda3\envs\autoGluon\lib\site-packages\transformers\models\llama\tokenization_llama.py:196, in LlamaTokenizer.get_spm_processor(self, from_slow)
194 tokenizer = spm.SentencePieceProcessor(**self.sp_model_kwargs)
195 if self.legacy or from_slow: # no dependency on protobuf
--> 196 tokenizer.Load(self.vocab_file)
197 return tokenizer
199 with open(self.vocab_file, "rb") as f:
File c:\Users\zhiyuanUSYD\miniconda3\envs\autoGluon\lib\site-packages\sentencepiece\init.py:961, in SentencePieceProcessor.Load(self, model_file, model_proto)
959 if model_proto:
960 return self.LoadFromSerializedProto(model_proto)
--> 961 return self.LoadFromFile(model_file)
File c:\Users\zhiyuanUSYD\miniconda3\envs\autoGluon\lib\site-packages\sentencepiece\init.py:316, in SentencePieceProcessor.LoadFromFile(self, arg)
315 def LoadFromFile(self, arg):
--> 316 return _sentencepiece.SentencePieceProcessor_LoadFromFile(self, arg)
TypeError: not a string"
}
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