zeevikal
commented
2 years ago @msl9810 hi, were you able to create/receive req.txt?
Open msl9810 opened 2 years ago
zeevikal
commented
2 years ago @msl9810 hi, were you able to create/receive req.txt?
msl9810
commented
2 years ago @msl9810 hi, were you able to create/receive req.txt? you can try create a virtual environment with tf1.8
zeevikal
commented
2 years ago @msl9810 were you able to load the w2v model? i have a gensim lib error while trying to load it.
msl9810
commented
2 years ago @msl9810 were you able to load the w2v model? i have a gensim lib error while trying to load it.
you can try gemsim3.8.3
zeevikal
commented
2 years ago @msl9810 were you able to load the w2v model? i have a gensim lib error while trying to load it.
you can try gemsim3.8.3
I used 3.8 with no success. were you able to run the w2v model? if so, please share your PyPI env/ requirements file. thanks.
msl9810
commented
2 years ago @msl9810 were you able to load the w2v model? i have a gensim lib error while trying to load it.
you can try gemsim3.8.3
I used 3.8 with no success. were you able to run the w2v model? if so, please share your PyPI env/ requirements file. thanks.
I trained the w2v by myself.The req.txt as follow:
_tflow_select=2.2.0=eigen absl-py=0.15.0=pyhd3eb1b0_0 adjusttext=0.7.3=pypi_0 aiohttp=3.7.4.post0=py36h2bbff1b_2 argon2-cffi=20.1.0=py36h2bbff1b_1 astor=0.8.1=py36haa95532_0 async-timeout=3.0.1=py36haa95532_0 async_generator=1.10=py36h28b3542_0 attrs=21.4.0=pyhd3eb1b0_0 backcall=0.2.0=pyhd3eb1b0_0 blas=1.0=mkl bleach=4.1.0=pyhd3eb1b0_0 boto3=1.20.24=pyhd3eb1b0_0 botocore=1.23.24=pyhd3eb1b0_0 brotlipy=0.7.0=py36h2bbff1b_1003 ca-certificates=2022.4.26=haa95532_0 cachetools=4.2.2=pyhd3eb1b0_0 certifi=2021.5.30=py36haa95532_0 cffi=1.14.6=py36h2bbff1b_0 chardet=4.0.0=py36haa95532_1003 charset-normalizer=2.0.4=pyhd3eb1b0_0 colorama=0.4.4=pyhd3eb1b0_0 coverage=5.5=py36h2bbff1b_2 cryptography=35.0.0=py36h71e12ea_0 cudatoolkit=9.0=1 cudnn=7.6.5=cuda9.0_0 cycler=0.11.0=pyhd3eb1b0_0 cython=0.29.24=py36hd77b12b_0 dataclasses=0.8=pyh4f3eec9_6 decorator=5.1.1=pyhd3eb1b0_0 defusedxml=0.7.1=pyhd3eb1b0_0 entrypoints=0.3=py36_0 freetype=2.10.4=hd328e21_0 gast=0.5.3=pyhd3eb1b0_0 gensim=3.8.3=py36hd77b12b_2 google-api-core=1.25.1=pyhd3eb1b0_0 google-auth=1.33.0=pyhd3eb1b0_0 google-cloud-core=1.7.1=pyhd3eb1b0_0 google-cloud-storage=1.41.0=pyhd3eb1b0_0 google-crc32c=1.1.2=py36h2bbff1b_0 google-resumable-media=1.3.1=pyhd3eb1b0_1 googleapis-common-protos=1.53.0=py36h2eaa2aa_0 grpcio=1.36.1=py36hc60d5dd_1 h5py=2.10.0=py36h5e291fa_0 hdf5=1.10.4=h7ebc959_0 icc_rt=2019.0.0=h0cc432a_1 icu=58.2=ha925a31_3 idna=3.3=pyhd3eb1b0_0 idna_ssl=1.1.0=py36haa95532_0 importlib-metadata=4.8.1=py36haa95532_0 importlib_metadata=4.8.1=hd3eb1b0_0 intel-openmp=2022.0.0=haa95532_3663 ipykernel=5.3.4=py36h5ca1d4c_0 ipython=7.16.1=py36h5ca1d4c_0 ipython_genutils=0.2.0=pyhd3eb1b0_1 ipywidgets=7.6.5=pyhd3eb1b0_1 jedi=0.17.0=py36_0 jinja2=3.0.3=pyhd3eb1b0_0 jmespath=0.10.0=pyhd3eb1b0_0 joblib=1.1.0=pypi_0 jpeg=9d=h2bbff1b_0 jsonschema=3.2.0=pyhd3eb1b0_2 jupyter=1.0.0=py36_7 jupyter_client=7.1.2=pyhd3eb1b0_0 jupyter_console=6.4.3=pyhd3eb1b0_0 jupyter_core=4.8.1=py36haa95532_0 jupyterlab_pygments=0.1.2=py_0 jupyterlab_widgets=1.0.0=pyhd3eb1b0_1 keras=2.2.4=0 keras-applications=1.0.8=py_1 keras-base=2.2.4=py36_0 keras-preprocessing=1.1.2=pyhd3eb1b0_0 kiwisolver=1.3.1=py36hd77b12b_0 libcrc32c=1.1.1=ha925a31_2 libpng=1.6.37=h2a8f88b_0 libprotobuf=3.17.2=h23ce68f_1 libtiff=4.2.0=hd0e1b90_0 lz4-c=1.9.3=h2bbff1b_1 m2w64-gcc-libgfortran=5.3.0=6 m2w64-gcc-libs=5.3.0=7 m2w64-gcc-libs-core=5.3.0=7 m2w64-gmp=6.1.0=2 m2w64-libwinpthread-git=5.0.0.4634.697f757=2 markdown=3.3.4=py36haa95532_0 markupsafe=2.0.1=py36h2bbff1b_0 matplotlib=3.3.4=py36haa95532_0 matplotlib-base=3.3.4=py36h49ac443_0 mistune=0.8.4=py36he774522_0 mkl=2020.2=256 mkl-service=2.3.0=py36h196d8e1_0 mkl_fft=1.3.0=py36h46781fe_0 mkl_random=1.1.1=py36h47e9c7a_0 msys2-conda-epoch=20160418=1 multidict=5.1.0=py36h2bbff1b_2 nbclient=0.5.3=pyhd3eb1b0_0 nbconvert=6.0.7=py36_0 nbformat=5.1.3=pyhd3eb1b0_0 nest-asyncio=1.5.1=pyhd3eb1b0_0 nltk=3.4.5=py36_0 notebook=6.4.3=py36haa95532_0 numpy=1.19.2=py36hadc3359_0 numpy-base=1.19.2=py36ha3acd2a_0 olefile=0.46=py36_0 openssl=1.1.1n=h2bbff1b_0 packaging=21.3=pyhd3eb1b0_0 pandas=1.1.5=py36hd77b12b_0 pandoc=2.12=haa95532_0 pandocfilters=1.5.0=pyhd3eb1b0_0 parso=0.8.3=pyhd3eb1b0_0 pickleshare=0.7.5=pyhd3eb1b0_1003 pillow=8.3.1=py36h4fa10fc_0 pip=21.2.2=py36haa95532_0 prometheus_client=0.13.1=pyhd3eb1b0_0 prompt-toolkit=3.0.20=pyhd3eb1b0_0 prompt_toolkit=3.0.20=hd3eb1b0_0 protobuf=3.17.2=py36hd77b12b_0 pyasn1=0.4.8=pyhd3eb1b0_0 pyasn1-modules=0.2.8=py_0 pycparser=2.21=pyhd3eb1b0_0 pygments=2.11.2=pyhd3eb1b0_0 pyopenssl=22.0.0=pyhd3eb1b0_0 pyparsing=3.0.4=pyhd3eb1b0_0 pyqt=5.9.2=py36h6538335_2 pyreadline=2.1=py36_1 pyrsistent=0.17.3=py36he774522_0 pysocks=1.7.1=py36haa95532_0 python=3.6.13=h3758d61_0 python-dateutil=2.8.2=pyhd3eb1b0_0 pytz=2021.3=pyhd3eb1b0_0 pywin32=228=py36hbaba5e8_1 pywinpty=0.5.7=py36_0 pyyaml=6.0=pypi_0 pyzmq=22.2.1=py36hd77b12b_1 qt=5.9.7=vc14h73c81de_0 qtconsole=5.2.2=pyhd3eb1b0_0 qtpy=1.11.2=pyhd3eb1b0_0 requests=2.27.1=pyhd3eb1b0_0 rsa=4.7.2=pyhd3eb1b0_1 s3transfer=0.5.0=pyhd3eb1b0_0 scikit-learn=0.24.2=pypi_0 scipy=1.5.2=py36h9439919_0 seaborn=0.11.2=pyhd3eb1b0_0 send2trash=1.8.0=pyhd3eb1b0_1 setuptools=58.0.4=py36haa95532_0 sip=4.19.8=py36h6538335_0 six=1.16.0=pyhd3eb1b0_1 sklearn=0.0=pypi_0 smart_open=5.1.0=pyhd3eb1b0_0 sqlite=3.38.0=h2bbff1b_0 tensorboard=1.10.0=py36he025d50_0 tensorflow=1.10.0=eigen_py36h849fbd8_0 tensorflow-base=1.10.0=eigen_py36h45df0d8_0 termcolor=1.1.0=py36haa95532_1 terminado=0.9.4=py36haa95532_0 testpath=0.5.0=pyhd3eb1b0_0 threadpoolctl=3.1.0=pypi_0 tk=8.6.11=h2bbff1b_0 tornado=6.1=py36h2bbff1b_0 traitlets=4.3.3=py36haa95532_0 typing-extensions=4.1.1=hd3eb1b0_0 typing_extensions=4.1.1=pyh06a4308_0 urllib3=1.26.8=pyhd3eb1b0_0 vc=14.2=h21ff451_1 vs2015_runtime=14.27.29016=h5e58377_2 wcwidth=0.2.5=pyhd3eb1b0_0 webencodings=0.5.1=py36_1 werkzeug=2.0.3=pyhd3eb1b0_0 wheel=0.37.1=pyhd3eb1b0_0 widgetsnbextension=3.5.1=py36_0 win_inet_pton=1.1.0=py36haa95532_0 wincertstore=0.2=py36h7fe50ca_0 winpty=0.4.3=4 xz=5.2.5=h62dcd97_0 yaml=0.2.5=he774522_0 yarl=1.5.1=py36he774522_0 zipp=3.6.0=pyhd3eb1b0_0 zlib=1.2.11=hbd8134f_5 zstd=1.4.9=h19a0ad4_0
zeevikal
commented
2 years ago @msl9810 thanks!
ghost
commented
1 year ago @msl9810 were you able to load the w2v model? i have a gensim lib error while trying to load it.
you can try gemsim3.8.3
hello, I would like to ask how long it took you to train the w2v model, I have been running for 48 hours on my machine and still not finished.
msl9810
commented
1 year ago @msl9810 were you able to load the w2v model? i have a gensim lib error while trying to load it.
you can try gemsim3.8.3
hello, I would like to ask how long it took you to train the w2v model, I have been running for 48 hours on my machine and still not finished.
这个要看你的设备具体是什么的吧？我用的是AMD的5800X，印象里完全用不了48小时这么久的。
ghost
commented
1 year ago @msl9810 were you able to load the w2v model? i have a gensim lib error while trying to load it.
you can try gemsim3.8.3
hello, I would like to ask how long it took you to train the w2v model, I have been running for 48 hours on my machine and still not finished.
这个要看你的设备具体是什么的吧？我用的是AMD的5800X，印象里完全用不了48小时这么久的。
原来是同胞啊，谢谢回答！我的设备是AMD Ryzen 5 5600X 6-Core Processor CPU ，卡在nltk.sent_tokenize那儿48小时了，不知道为啥，请问你之前在运行的时候遇到过这个问题吗？
ghost
commented
1 year ago @msl9810 were you able to load the w2v model? i have a gensim lib error while trying to load it.
you can try gemsim3.8.3
hello, I would like to ask how long it took you to train the w2v model, I have been running for 48 hours on my machine and still not finished.
这个要看你的设备具体是什么的吧？我用的是AMD的5800X，印象里完全用不了48小时这么久的。
原来是同胞啊，谢谢回答！我的设备是AMD Ryzen 5 5600X 6-Core Processor CPU ，卡在nltk.sent_tokenize那儿48小时了，不知道为啥，请问你之前在运行的时候遇到过这个问题吗？
还有请问你之前在加载原作者提供的word2vec.model的时候是否遇到过No such file or directory: '...word2vec_withString10-100-200.model.wv.vectors.npy这个报错，这是因为gensim的版本问题还是加载时缺少运行文件问题？真诚的感谢你！
msl9810
commented
1 year ago @msl9810 were you able to load the w2v model? i have a gensim lib error while trying to load it.
you can try gemsim3.8.3
hello, I would like to ask how long it took you to train the w2v model, I have been running for 48 hours on my machine and still not finished.
这个要看你的设备具体是什么的吧？我用的是AMD的5800X，印象里完全用不了48小时这么久的。
原来是同胞啊，谢谢回答！我的设备是AMD Ryzen 5 5600X 6-Core Processor CPU ，卡在nltk.sent_tokenize那儿48小时了，不知道为啥，请问你之前在运行的时候遇到过这个问题吗？
虽然CPU性能上有点差距但是不至于到48小时这么离谱，我感觉
@msl9810 were you able to load the w2v model? i have a gensim lib error while trying to load it.
you can try gemsim3.8.3
hello, I would like to ask how long it took you to train the w2v model, I have been running for 48 hours on my machine and still not finished.
这个要看你的设备具体是什么的吧？我用的是AMD的5800X，印象里完全用不了48小时这么久的。
原来是同胞啊，谢谢回答！我的设备是AMD Ryzen 5 5600X 6-Core Processor CPU ，卡在nltk.sent_tokenize那儿48小时了，不知道为啥，请问你之前在运行的时候遇到过这个问题吗？
还有请问你之前在加载原作者提供的word2vec.model的时候是否遇到过No such file or directory: '...word2vec_withString10-100-200.model.wv.vectors.npy这个报错，这是因为gensim的版本问题还是加载时缺少运行文件问题？真诚的感谢你！ 我是很久之前运行的代码了，细节已经忘得差不多了。我觉得大概率还是库版本的问题，我当时也是没法直接加载作者训练好的模型所以才自己训练word2vec。印象里word2vec训练起来用时不是特别长，即使我们的CPU性能上有点差距也到不了48小时这么离谱。我觉得你可以试试训练时输出点什么避免单纯卡住了的情况，，，
ghost
commented
1 year ago @msl9810 were you able to load the w2v model? i have a gensim lib error while trying to load it.
you can try gemsim3.8.3
hello, I would like to ask how long it took you to train the w2v model, I have been running for 48 hours on my machine and still not finished.
这个要看你的设备具体是什么的吧？我用的是AMD的5800X，印象里完全用不了48小时这么久的。
原来是同胞啊，谢谢回答！我的设备是AMD Ryzen 5 5600X 6-Core Processor CPU ，卡在nltk.sent_tokenize那儿48小时了，不知道为啥，请问你之前在运行的时候遇到过这个问题吗？
虽然CPU性能上有点差距但是不至于到48小时这么离谱，我感觉
@msl9810 were you able to load the w2v model? i have a gensim lib error while trying to load it.
you can try gemsim3.8.3
hello, I would like to ask how long it took you to train the w2v model, I have been running for 48 hours on my machine and still not finished.
这个要看你的设备具体是什么的吧？我用的是AMD的5800X，印象里完全用不了48小时这么久的。
原来是同胞啊，谢谢回答！我的设备是AMD Ryzen 5 5600X 6-Core Processor CPU ，卡在nltk.sent_tokenize那儿48小时了，不知道为啥，请问你之前在运行的时候遇到过这个问题吗？
还有请问你之前在加载原作者提供的word2vec.model的时候是否遇到过No such file or directory: '...word2vec_withString10-100-200.model.wv.vectors.npy这个报错，这是因为gensim的版本问题还是加载时缺少运行文件问题？真诚的感谢你！ 我是很久之前运行的代码了，细节已经忘得差不多了。我觉得大概率还是库版本的问题，我当时也是没法直接加载作者训练好的模型所以才自己训练word2vec。印象里word2vec训练起来用时不是特别长，即使我们的CPU性能上有点差距也到不了48小时这么离谱。我觉得你可以试试训练时输出点什么避免单纯卡住了的情况，，，
好的，谢谢老哥热心的回答！！！
Byhas
commented
2 months ago please provide me a requierments.txt file
I hasn't find the env to run the example.So maybe you can share the requirements.txt?