- clarifai
- sentiment-analysis
multilingual-sentiment-analysis-bert
Workflow uses the Bert-base-multilingual-uncased Model tailored specifically for multilingual sentiment analysis.
Notes
Multilingual Sentiment Analysis
This workflow uses the Bert-base-multilingual-uncased Model tailored specifically for multilingual sentiment analysis.
Bert-base-multilingual-uncased Model
Bert-base-multilingual-uncased model fine-tuned for sentiment analysis on product reviews in six languages: English, Dutch, German, French, Spanish and Italian. It predicts the sentiment of the review as a number of stars (between 1 and 5). This model is intended for direct use as a sentiment analysis model for product reviews in any of the six languages above, or for further finetuning on related sentiment analysis tasks.
How to use the Financial sentiments Analysis workflow?
Using Clarifai SDK
Export your PAT as an environment variable. Then, import and initialize the API Client.
Find your PAT in your security settings.
export CLARIFAI_PAT={your personal access token}
Prediction with the workflow
from clarifai.client.workflow import Workflow
workflow_url = 'https://clarifai.com/clarifai/sentiment-analysis/workflows/multilingual-sentiment-analysis-bert'
text = 'I love this movie and i would watch it again and again!'
prediction = Workflow(workflow_url).predict_by_bytes(text.encode(), input_type="text")
# Get workflow results
print(prediction.results[0].outputs[-1].data)
Using Workflow
To utilize the Multilingual sentiments Analysis workflow, you can input text through the Blue Plus Try your own Input button and it will provide whether the sentiment is positive, negative, or neutral.
- Workflow IDmultilingual-sentiment-analysis-bert
- DescriptionWorkflow uses the Bert-base-multilingual-uncased Model tailored specifically for multilingual sentiment analysis.
- Last UpdatedApr 08, 2024
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