Comments (7)
Schluca
commented on May 18, 2024
1
I had the same issue. I think it is caused by installing a newer version of transformers (4.6.1) while aspect-based-sentiment-analysis needs 2.5.0. Could also be caused by a different library that is updated by newer versions of transformers.
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AschHarwood
commented on May 18, 2024
I'm having the exact same problem.
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mileschandler
commented on May 18, 2024
same issue. bump
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mileschandler
commented on May 18, 2024
Note. This is likely a dependency issue @AschHarwood . If you create a conda env using the environment.yml mine works fine.
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Nikola1023
commented on May 18, 2024
Has anyone solved the problem? I have the same issue.
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tatiana-norkina
commented on May 18, 2024
the code works if you run in google colab
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arditobryan
commented on May 18, 2024
Running in the same issue, (installation for transformers 2.5.0 is also very problematic, so far unable to try this fix)
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Related Issues (20)
- Error running Pipeline with BasicReferenceRecognizer HOT 2
- Fine-tuning the model to add specific words and phrases with polarity HOT 1
- GPU usage with Large Data during prediction HOT 1
- Type mismatch error during operation on `scores` array HOT 1
- Getting Error while calling BERTClassifier HOT 4
- How to fine tune this model HOT 1
- Performs invalid character removal and whitespace cleanup on text
- Getting error from professor file! HOT 1
- Getting error with basic first code HOT 5
- numpy-1.19.5-cp37-cp37m-manylinux2010_x86_64.whl: 2 vulnerabilities (highest severity is: 5.3)
- Disabling the computation and output of Attention and Interpretation results
- Werkzeug-2.2.2-py3-none-any.whl: 4 vulnerabilities (highest severity is: 7.5)
- Question about this ABSA package integration with the 🤗Transformers pipeline
- scipy-1.7.3-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl: 2 vulnerabilities (highest severity is: 9.8) - autoclosed HOT 1
- grpcio-1.34.1-cp37-cp37m-manylinux2014_x86_64.whl: 1 vulnerabilities (highest severity is: 7.5) - autoclosed HOT 1
- urllib3-1.26.13-py2.py3-none-any.whl: 2 vulnerabilities (highest severity is: 8.1)
- transformers-4.8.2-py3-none-any.whl: 4 vulnerabilities (highest severity is: 8.8)
- certifi-2022.12.7-py3-none-any.whl: 1 vulnerabilities (highest severity is: 9.8)
- requests-2.28.1-py3-none-any.whl: 1 vulnerabilities (highest severity is: 6.1)
- Jinja2-3.1.2-py3-none-any.whl: 2 vulnerabilities (highest severity is: 6.1)
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