lordjia/Llama-3-Cantonese-8B-Instruct
Llama-3-Cantonese-8B-Instruct by lordjia is an 8 billion parameter language model based on Meta-Llama-3-8B-Instruct, fine-tuned using LoRA. It is specifically optimized to enhance Cantonese text generation and comprehension, supporting tasks like dialogue, summarization, and question-answering. This model leverages Cantonese-specific datasets to improve its performance in the primary language. A 4-bit quantized version is also available for efficient deployment.
Loading preview...
Model Overview
Llama-3-Cantonese-8B-Instruct is an 8 billion parameter language model developed by lordjia, built upon the Meta-Llama-3-8B-Instruct architecture. It has been fine-tuned using the LoRA method over 4562 steps, specifically to improve its capabilities in the Cantonese language.
Key Capabilities
- Enhanced Cantonese Processing: Designed to boost Cantonese text generation and understanding.
- Versatile Task Support: Capable of handling various natural language tasks, including dialogue generation, text summarization, and question-answering in Cantonese.
- Specialized Training Data: Fine-tuned on dedicated Cantonese datasets, including
jed351/cantonese-wikipediaandlordjia/Cantonese_English_Translation, to ensure high linguistic relevance. - Quantized Version Available: A 4-bit quantized version (
llama3-cantonese-8b-instruct-q4_0.gguf) is provided for more efficient inference and deployment.
Performance Insights
Evaluations on the Open LLM Leaderboard show an average score of 24.16. Specific metrics include 66.69 for IFEval (0-Shot), 26.79 for BBH (3-Shot), and 27.94 for MMLU-PRO (5-shot).
Good For
- Developers and researchers focusing on Cantonese language applications.
- Projects requiring robust Cantonese dialogue, summarization, or Q&A functionalities.
- Use cases where a specialized, instruction-tuned Cantonese model is preferred over general-purpose LLMs.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.