seandearnaley/llama3-8b-sentiment-may-3-2024
seandearnaley/llama3-8b-sentiment-may-3-2024 is an 8 billion parameter Llama 3 model developed by seandearnaley, fine-tuned for sentiment analysis. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is optimized for sentiment classification tasks, leveraging its 8192-token context length for nuanced understanding.
Loading preview...
Model Overview
seandearnaley/llama3-8b-sentiment-may-3-2024 is an 8 billion parameter Llama 3 model, developed by seandearnaley, specifically fine-tuned for sentiment analysis. This model leverages the Llama 3 architecture and was trained using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
Key Capabilities
- Sentiment Analysis: Optimized for classifying the sentiment of text inputs.
- Efficient Training: Benefits from Unsloth's accelerated training techniques.
- Llama 3 Foundation: Built upon the robust Llama 3 8B Instruct base model.
Good For
- Applications requiring efficient and accurate sentiment classification.
- Developers looking for a Llama 3-based model with specialized sentiment capabilities.
- Use cases where faster fine-tuning methods are advantageous.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.