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The most recent LLaMA-3-70B Instruct showcases the beast performance in zero-shot-learning mode in Target-Sentiment-Analsys (TSA) 🔥🚀  In particular we experiment with sentence-level analysis, with sentences fetched from the WikiArticles that were formed into RuSentNE-2023 dataset. 
The most recent LLaMA-3-70B Instruct showcases the beast performance in zero-shot-learning mode in Target-Sentiment-Analsys (TSA) 🔥🚀  In particular we experiment with sentence-level analysis, with sentences fetched from the WikiArticles that were formed into RuSentNE-2023 dataset. 
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The key takeaways out of LLaMA-3-70B performance on original (🇷🇺) texts and translated into English are as follows:
The key takeaways out of LLaMA-3-70B performance on original (🇷🇺) texts and translated into English are as follows:
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1. Outperforms all ChatGPT-4 and all predecessors on non-english-texts (🇷🇺) 
1. Outperforms all ChatGPT-4 and all predecessors on non-english-texts (🇷🇺) 
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2. Surpasses all ChatGPT-3.5 / nearly performs as good as ChatGPT-4 on english texts 🥳
2. Surpasses all ChatGPT-3.5 / nearly performs as good as ChatGPT-4 on english texts 🥳
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Benchmark: 
Benchmark: 
link
https://github.com/nicolay-r/RuSentNE-LLM-Benchmark
https://github.com/nicolay-r/RuSentNE-LLM-Benchmark
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Model: 
Model: 
resource
https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct
model
meta-llama/Meta-Llama-3-70B-Instruct
https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct
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Dataset: 
Dataset: 
link
https://github.com/dialogue-evaluation/RuSentNE-evaluation
https://github.com/dialogue-evaluation/RuSentNE-evaluation
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Related paper: 
Related paper: 
resource
https://huggingface.co/papers/2404.12342
paper
2404.12342
https://huggingface.co/papers/2404.12342
Large Language Models in Targeted Sentiment Analysis (2404.12342)
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Collection: 
Collection: 
link
https://huggingface.co/collections/nicolay-r/sentiment-analysis-665ba391e0eba729021ea101
https://huggingface.co/collections/nicolay-r/sentiment-analysis-665ba391e0eba729021ea101
The most recent LLaMA-3-70B Instruct showcases the beast performance in zero-shot-learning mode in Target-Sentiment-Analsys (TSA) 🔥🚀  In particular we experiment with sentence-level analysis, with sentences fetched from the WikiArticles that were formed into RuSentNE-2023 dataset. 

The key takeaways out of LLaMA-3-70B performance on original (🇷🇺) texts and translated into English are as follows:
1. Outperforms all ChatGPT-4 and all predecessors on non-english-texts (🇷🇺) 
2. Surpasses all ChatGPT-3.5 / nearly performs as good as ChatGPT-4 on english texts 🥳

Benchmark: https://github.com/nicolay-r/RuSentNE-LLM-Benchmark
Model: https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct
Dataset: https://github.com/dialogue-evaluation/RuSentNE-evaluation
Related paper: https://huggingface.co/papers/2404.12342
Collection: https://huggingface.co/collections/nicolay-r/sentiment-analysis-665ba391e0eba729021ea101
🔥
victor-huang kristaller486 Taylor658 Kirkalish Tanvir1337 osanseviero Rohith04 den0620