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classifier = pipeline("sentiment-analysis")
updated to LLAmA2 model for text generation
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Closes #issue-number
Description
i suggests that using LLaMA2 model for better text generation by integrating the fine tuned LLaMA2 model on sentiment analysis dataset we can achieve a better performance for texting in positively and negatively to the prompt. #246( gh pr checkout 246)
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[ ] Bug fix
[ ] Feature enhancement
[ ] Documentation update
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from transformers import pipeline
Sentiment analysis pipeline
classifier = pipeline("sentiment-analysis") updated to LLAmA2 model for text generation
Related Issue
[Cite any related issue(s) this pull request addresses. If none, simply state “None”]
NOTE: Kindly write in the following format -
Closes #issue-number
Description
i suggests that using LLaMA2 model for better text generation by integrating the fine tuned LLaMA2 model on sentiment analysis dataset we can achieve a better performance for texting in positively and negatively to the prompt. #246( gh pr checkout 246)
Type of PR
Screenshots / videos (if applicable)
[Attach any relevant screenshots or videos demonstrating the changes]
Checklist:
Additional context:
[Include any additional information or context that might be helpful for reviewers.]