sentimental-analysis-dbrx

Sentiment Analysis

Large Language Models (LLMs), like GPT (Generative Pretrained Transformer) variants, since they are pre-trained on diverse internet text, enabling them to understand context, nuance, and the subtleties of human language, making them particularly adept at detecting sentiments within text, ranging from basic positive/negative judgments to more complex emotional analyses.

sentimental-analysis-dbrx 

Workflow uses DBRX-Instruct Model with specified prompt template for sentimental analysis and Provide a sentiment score from -1 (most negative) to 1 (most positive) and predicts if the input text is positive/negative or neural sentiment.  

How to use the sentimental-analysis-mistral-7b 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/sentimental-analysis-dbrx'

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 Sentiment 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.