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### Short description of current behavior
I have huggingface sentiment analyzer and sentiment explain comes as text in next format:
```
{'Neutral': 0.6581241488456726, 'Bullish': 0.3416257798671722…
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**Please describe the module you would like to add to bricks**
We have some sentiment classification bricks, but only for English. It would be cool to have one for different languages, for example, G…
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**Please describe the module you would like to add to bricks**
I have fine-tuned a BERT model on a lot of stock news. The model can be used via the HuggingFace inference api.
**Do you already have…
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@QuinnHe @alanvww I suggest to change **Learning** to **Learn** for consistency.
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Hey!
I'm testing your model in another dataset. The WO and Sent Acc were used as metric in your paper. Did you provide them in this repo ?
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Hi, I tried only the first lines of code that were :
```
import aspect_based_sentiment_analysis as absa
nlp = absa.load()
text = ("We are great fans of Slack, but we wish the subscriptions "
…
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In the notebook `example/2022-12-10-textrl-elon-musk.ipynb`, the reward calculation in the `MyRLEnv` class should be updated for correct scoring. Specifically, the function `get_reward` needs modifica…
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Part of the web interface is supposed to show how each feature would be classified if it was a document of length one. Why does the hierarchical sentiment classifier only label these individual featur…
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Hi @Sachin19,
I checked the sentiment related scripts you kindly pushed to the repository!
And there were a minor correction and a question regarding them.
1. I think in line 31 of your readme …
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- Train a machine learning model (e.g., image classifier, sentiment analysis) and deploy it as a web service using Flask or FastAPI.